how long are thesis supposed to be

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How long are thesis statements? [with examples]

What is the proper length of a thesis statement?

Examples of thesis statements, frequently asked questions about the length of thesis statements, related articles.

If you find yourself in the process of writing a thesis statement but you don't know how long it should be, you've come to right place. In the next paragraphs you will learn about the most efficient way to write a thesis statement and how long it should be.

A thesis statement is a concise description of your work’s aim.

The short answer is: one or two sentences. The more i n-depth answer: as your writing evolves, and as you write longer papers, your thesis statement will typically be at least two, and often more, sentences. The thesis of a scholarly article may have three or four long sentences.

The point is to write a well-formed statement that clearly sets out the argument and aim of your research. A one sentence thesis is fine for shorter papers, but make sure it's a full, concrete statement. Longer thesis statements should follow the same rule; be sure that your statement includes essential information and resist too much exposition.

Here are some basic rules for thesis statement lengths based on the number of pages:

• 5 pages : 1 sentence
• 5-8 pages : 1 or 2 sentences
• 8-13 pages : 2 or 3 sentences
• 13-23 pages : 3 or 4 sentences
• Over 23 pages : a few sentences or a paragraph

Joe Haley, a former writing instructor at Johns Hopkins University exemplified in this forum post the different sizes a thesis statement can take. For a paper on Jane Austen's  Pride and Prejudice,  someone could come up with these two theses:

In Jane Austen's  Pride and Prejudice , gossip is an important but morally ambiguous tool for shaping characters' opinions of each other.

As the aforementioned critics have noted, the prevalence of gossip in Jane Austen's  oeuvre  does indeed reflect the growing prominence of an explicitly-delineated private sphere in nineteenth-century British society. However, in contrast with these critics' general conclusions about Austen and class, which tend to identify her authorial voice directly with the bourgeois mores shaping her appropriation of the  bildungsroman,  the ambiguity of this communicative mode in  Pride and Prejudice  suggests that when writing at the height of her authorial powers, at least, Austen is capable of skepticism and even self-critique. For what is the narrator of her most celebrated novel if not its arch-gossip  par excellence ?

Both statements are equally sound, but the second example clearly belongs in a longer paper. In the end, the length of your thesis statement will depend on the scope of your work.

There is no exact word count for a thesis statement, since the length depends on your level of knowledge and expertise. A two sentence thesis statement would be between 20-50 words.

The length of the work will determine how long your thesis statement is. A concise thesis is typically between 20-50 words. A paragraph is also acceptable for a thesis statement; however, anything over one paragraph is probably too long.

Here is a list of Thesis Statement Examples that will help you understand better how long they can be.

As a high school student, you are not expected to have an elaborate thesis statement. A couple of clear sentences indicating the aim of your essay will be more than enough.

Here is a YouTube tutorial that will help you write a thesis statement: How To Write An Essay: Thesis Statements by Ariel Bisset.

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How Long Should a Thesis Statement Be?

Students often ask how long should a thesis statement be when given a paper to write. This article addresses frequently asked questions concerning thesis statements and other relevant issues. We will answer several questions, including how many words in a thesis and how long should a thesis statement be.

How Long is a Thesis Statement, and Where Should it Be?

How long can a thesis statement be and not be, how long should a thesis statement be for a high school student, how many sentences are in a thesis statement, how long should a thesis paper be, how long is a thesis supposed to be for high school essay, how long are thesis statements for college essays, what is the length of a typical thesis statement for professional research papers, how long does a thesis paper have to be.

How long is a thesis paper that determines many things and has brought about several questions like how many words should a thesis statement be? It should not be too long, thirty to forty words at the most. As a rule, your thesis statement should reflect your knowledge and the scope of the essay you are writing. Whether you are writing an analytical research paper or an essay, the thesis statement should be in the introduction part. Your thesis should be at the beginning of the paper, preferably in the first paragraph.

A too-short thesis statement won’t give the sufficient information an audience needs, while one too long will be offering too much. This is something to keep in mind when researching; how long should a thesis statement be? Regardless of how long your essay or research paper is, your thesis statement should explain your position in short sentences. That means it should be convincing enough to get your audience interested in your point of view. Your thesis statement should not exceed one paragraph, whether you’re writing a school essay or an in-depth research paper.

If you’re writing a paper in high school, your thesis shouldn’t be more than two sentences long. Your teacher doesn’t expect you to have an extremely elaborate thesis statement as a high school student. So, one or two short sentences indicating your essay’s aim should be more than enough. Knowing how many sentences are in a thesis statement helps ensure you don’t overdo it.

How many sentences should a thesis statement depend on what type of paper you are writing? A thesis statement should normally be no more than two sentences long unless you are writing a very long paper. Your thesis statement should be short and straight to the point, declaring your specific position on the topic you’re writing on.

A good thesis will strike the right balance between not having a flat thesis and not giving too much information. How many sentences are in a thesis determines how many should be in a thesis statement?

A thesis paper is usually forty pages long, but it varies significantly from project to project and from one expertise level to another. This number includes texts, figures, and a list of references, but it doesn’t include appendices. Also, don’t take these generalizations on how long should a thesis be too seriously, especially if you’re working on a labor-intensive project.

How Many Words is a Thesis?

How long a thesis is usually around eighty to a hundred thousand words long, depending on the topic’s depth. At the master’s or college level, a thesis fluctuates between fifteen and twenty thousand words. However, research journals ask for articles no more than three to five thousand words. After knowing how long is a thesis, the next question is, how long should your thesis statement be?

Your thesis in high school should be short, depending on what topic you are working on. It is better to contain one concise sentence, clearly stating your thoughts on the topic. It is this thought you’ll expound on later in the essay. Always ask your teacher or instructor for clarity on how long is a thesis statement.

A college thesis statement’s length depends on how many sentences is a thesis and how many points a writer mentions. It should contain at least two clauses, an independent clause, your opinion, and a dependent clause, the reasons. It would help if you aimed for a single sentence at least two lines long, or at most forty words long.

A typical thesis statement for professional research papers is usually no more than fifty words long. However, thesis statements don’t exactly have an exact word count, but most experts advise staying within that range. Once you know how long are thesis papers, you’ll have an idea of how long a thesis statement should be.

A single sentence clearly stating your position is great, but it may be hard to compress all your thoughts into one sentence. Thus, if you can’t do one sentence, you can keep it to two, four at the most, lines in a paragraph.

Your thesis paper has to be as long as the instructions say; there is no one-rule-fits-all answer to this question. If you’re writing a thesis paper in college, it wouldn’t be as long as writing a Ph.D. thesis paper . A thesis length is at least three thousand words and at most a hundred thousand. How long should a thesis be in an essay is a common question for people new to writing professional research papers.

Your thesis statement may be short or long, depending on your academic level. While there is no one rule on how long is a thesis statement supposed to be, experts advise 20-50 words. Long or short, your thesis should clearly state your paper’s aim in one to four lines; leave out irrelevant words. If you need professional help writing your thesis, you can contact our expert team to give you the best services.

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Think of yourself as a member of a jury, listening to a lawyer who is presenting an opening argument. You'll want to know very soon whether the lawyer believes the accused to be guilty or not guilty, and how the lawyer plans to convince you. Readers of academic essays are like jury members: before they have read too far, they want to know what the essay argues as well as how the writer plans to make the argument. After reading your thesis statement, the reader should think, "This essay is going to try to convince me of something. I'm not convinced yet, but I'm interested to see how I might be."

An effective thesis cannot be answered with a simple "yes" or "no." A thesis is not a topic; nor is it a fact; nor is it an opinion. "Reasons for the fall of communism" is a topic. "Communism collapsed in Eastern Europe" is a fact known by educated people. "The fall of communism is the best thing that ever happened in Europe" is an opinion. (Superlatives like "the best" almost always lead to trouble. It's impossible to weigh every "thing" that ever happened in Europe. And what about the fall of Hitler? Couldn't that be "the best thing"?)

A good thesis has two parts. It should tell what you plan to argue, and it should "telegraph" how you plan to argue—that is, what particular support for your claim is going where in your essay.

Steps in Constructing a Thesis

First, analyze your primary sources.  Look for tension, interest, ambiguity, controversy, and/or complication. Does the author contradict himself or herself? Is a point made and later reversed? What are the deeper implications of the author's argument? Figuring out the why to one or more of these questions, or to related questions, will put you on the path to developing a working thesis. (Without the why, you probably have only come up with an observation—that there are, for instance, many different metaphors in such-and-such a poem—which is not a thesis.)

Once you have a working thesis, write it down.  There is nothing as frustrating as hitting on a great idea for a thesis, then forgetting it when you lose concentration. And by writing down your thesis you will be forced to think of it clearly, logically, and concisely. You probably will not be able to write out a final-draft version of your thesis the first time you try, but you'll get yourself on the right track by writing down what you have.

Keep your thesis prominent in your introduction.  A good, standard place for your thesis statement is at the end of an introductory paragraph, especially in shorter (5-15 page) essays. Readers are used to finding theses there, so they automatically pay more attention when they read the last sentence of your introduction. Although this is not required in all academic essays, it is a good rule of thumb.

Anticipate the counterarguments.  Once you have a working thesis, you should think about what might be said against it. This will help you to refine your thesis, and it will also make you think of the arguments that you'll need to refute later on in your essay. (Every argument has a counterargument. If yours doesn't, then it's not an argument—it may be a fact, or an opinion, but it is not an argument.)

This statement is on its way to being a thesis. However, it is too easy to imagine possible counterarguments. For example, a political observer might believe that Dukakis lost because he suffered from a "soft-on-crime" image. If you complicate your thesis by anticipating the counterargument, you'll strengthen your argument, as shown in the sentence below.

Some Caveats and Some Examples

A thesis is never a question.  Readers of academic essays expect to have questions discussed, explored, or even answered. A question ("Why did communism collapse in Eastern Europe?") is not an argument, and without an argument, a thesis is dead in the water.

A thesis is never a list.  "For political, economic, social and cultural reasons, communism collapsed in Eastern Europe" does a good job of "telegraphing" the reader what to expect in the essay—a section about political reasons, a section about economic reasons, a section about social reasons, and a section about cultural reasons. However, political, economic, social and cultural reasons are pretty much the only possible reasons why communism could collapse. This sentence lacks tension and doesn't advance an argument. Everyone knows that politics, economics, and culture are important.

A thesis should never be vague, combative or confrontational.  An ineffective thesis would be, "Communism collapsed in Eastern Europe because communism is evil." This is hard to argue (evil from whose perspective? what does evil mean?) and it is likely to mark you as moralistic and judgmental rather than rational and thorough. It also may spark a defensive reaction from readers sympathetic to communism. If readers strongly disagree with you right off the bat, they may stop reading.

An effective thesis has a definable, arguable claim.  "While cultural forces contributed to the collapse of communism in Eastern Europe, the disintegration of economies played the key role in driving its decline" is an effective thesis sentence that "telegraphs," so that the reader expects the essay to have a section about cultural forces and another about the disintegration of economies. This thesis makes a definite, arguable claim: that the disintegration of economies played a more important role than cultural forces in defeating communism in Eastern Europe. The reader would react to this statement by thinking, "Perhaps what the author says is true, but I am not convinced. I want to read further to see how the author argues this claim."

A thesis should be as clear and specific as possible.  Avoid overused, general terms and abstractions. For example, "Communism collapsed in Eastern Europe because of the ruling elite's inability to address the economic concerns of the people" is more powerful than "Communism collapsed due to societal discontent."

Copyright 1999, Maxine Rodburg and The Tutors of the Writing Center at Harvard University

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Tips and Examples for Writing Thesis Statements

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Tips for Writing Your Thesis Statement

1. Determine what kind of paper you are writing:

• An analytical paper breaks down an issue or an idea into its component parts, evaluates the issue or idea, and presents this breakdown and evaluation to the audience.
• An expository (explanatory) paper explains something to the audience.
• An argumentative paper makes a claim about a topic and justifies this claim with specific evidence. The claim could be an opinion, a policy proposal, an evaluation, a cause-and-effect statement, or an interpretation. The goal of the argumentative paper is to convince the audience that the claim is true based on the evidence provided.

If you are writing a text that does not fall under these three categories (e.g., a narrative), a thesis statement somewhere in the first paragraph could still be helpful to your reader.

2. Your thesis statement should be specific—it should cover only what you will discuss in your paper and should be supported with specific evidence.

3. The thesis statement usually appears at the end of the first paragraph of a paper.

4. Your topic may change as you write, so you may need to revise your thesis statement to reflect exactly what you have discussed in the paper.

Thesis Statement Examples

Example of an analytical thesis statement:

The paper that follows should:

• Explain the analysis of the college admission process
• Explain the challenge facing admissions counselors

Example of an expository (explanatory) thesis statement:

• Explain how students spend their time studying, attending class, and socializing with peers

Example of an argumentative thesis statement:

• Present an argument and give evidence to support the claim that students should pursue community projects before entering college

Thesis Statements

What this handout is about.

This handout describes what a thesis statement is, how thesis statements work in your writing, and how you can craft or refine one for your draft.

Introduction

Writing in college often takes the form of persuasion—convincing others that you have an interesting, logical point of view on the subject you are studying. Persuasion is a skill you practice regularly in your daily life. You persuade your roommate to clean up, your parents to let you borrow the car, your friend to vote for your favorite candidate or policy. In college, course assignments often ask you to make a persuasive case in writing. You are asked to convince your reader of your point of view. This form of persuasion, often called academic argument, follows a predictable pattern in writing. After a brief introduction of your topic, you state your point of view on the topic directly and often in one sentence. This sentence is the thesis statement, and it serves as a summary of the argument you’ll make in the rest of your paper.

What is a thesis statement?

A thesis statement:

• tells the reader how you will interpret the significance of the subject matter under discussion.
• is a road map for the paper; in other words, it tells the reader what to expect from the rest of the paper.
• directly answers the question asked of you. A thesis is an interpretation of a question or subject, not the subject itself. The subject, or topic, of an essay might be World War II or Moby Dick; a thesis must then offer a way to understand the war or the novel.
• makes a claim that others might dispute.
• is usually a single sentence near the beginning of your paper (most often, at the end of the first paragraph) that presents your argument to the reader. The rest of the paper, the body of the essay, gathers and organizes evidence that will persuade the reader of the logic of your interpretation.

If your assignment asks you to take a position or develop a claim about a subject, you may need to convey that position or claim in a thesis statement near the beginning of your draft. The assignment may not explicitly state that you need a thesis statement because your instructor may assume you will include one. When in doubt, ask your instructor if the assignment requires a thesis statement. When an assignment asks you to analyze, to interpret, to compare and contrast, to demonstrate cause and effect, or to take a stand on an issue, it is likely that you are being asked to develop a thesis and to support it persuasively. (Check out our handout on understanding assignments for more information.)

How do I create a thesis?

A thesis is the result of a lengthy thinking process. Formulating a thesis is not the first thing you do after reading an essay assignment. Before you develop an argument on any topic, you have to collect and organize evidence, look for possible relationships between known facts (such as surprising contrasts or similarities), and think about the significance of these relationships. Once you do this thinking, you will probably have a “working thesis” that presents a basic or main idea and an argument that you think you can support with evidence. Both the argument and your thesis are likely to need adjustment along the way.

Writers use all kinds of techniques to stimulate their thinking and to help them clarify relationships or comprehend the broader significance of a topic and arrive at a thesis statement. For more ideas on how to get started, see our handout on brainstorming .

How do I know if my thesis is strong?

If there’s time, run it by your instructor or make an appointment at the Writing Center to get some feedback. Even if you do not have time to get advice elsewhere, you can do some thesis evaluation of your own. When reviewing your first draft and its working thesis, ask yourself the following :

• Do I answer the question? Re-reading the question prompt after constructing a working thesis can help you fix an argument that misses the focus of the question. If the prompt isn’t phrased as a question, try to rephrase it. For example, “Discuss the effect of X on Y” can be rephrased as “What is the effect of X on Y?”
• Have I taken a position that others might challenge or oppose? If your thesis simply states facts that no one would, or even could, disagree with, it’s possible that you are simply providing a summary, rather than making an argument.
• Is my thesis statement specific enough? Thesis statements that are too vague often do not have a strong argument. If your thesis contains words like “good” or “successful,” see if you could be more specific: why is something “good”; what specifically makes something “successful”?
• Does my thesis pass the “So what?” test? If a reader’s first response is likely to  be “So what?” then you need to clarify, to forge a relationship, or to connect to a larger issue.
• Does my essay support my thesis specifically and without wandering? If your thesis and the body of your essay do not seem to go together, one of them has to change. It’s okay to change your working thesis to reflect things you have figured out in the course of writing your paper. Remember, always reassess and revise your writing as necessary.
• Does my thesis pass the “how and why?” test? If a reader’s first response is “how?” or “why?” your thesis may be too open-ended and lack guidance for the reader. See what you can add to give the reader a better take on your position right from the beginning.

Suppose you are taking a course on contemporary communication, and the instructor hands out the following essay assignment: “Discuss the impact of social media on public awareness.” Looking back at your notes, you might start with this working thesis:

Social media impacts public awareness in both positive and negative ways.

You can use the questions above to help you revise this general statement into a stronger thesis.

• Do I answer the question? You can analyze this if you rephrase “discuss the impact” as “what is the impact?” This way, you can see that you’ve answered the question only very generally with the vague “positive and negative ways.”
• Have I taken a position that others might challenge or oppose? Not likely. Only people who maintain that social media has a solely positive or solely negative impact could disagree.
• Is my thesis statement specific enough? No. What are the positive effects? What are the negative effects?
• Does my thesis pass the “how and why?” test? No. Why are they positive? How are they positive? What are their causes? Why are they negative? How are they negative? What are their causes?
• Does my thesis pass the “So what?” test? No. Why should anyone care about the positive and/or negative impact of social media?

After thinking about your answers to these questions, you decide to focus on the one impact you feel strongly about and have strong evidence for:

Because not every voice on social media is reliable, people have become much more critical consumers of information, and thus, more informed voters.

This version is a much stronger thesis! It answers the question, takes a specific position that others can challenge, and it gives a sense of why it matters.

Let’s try another. Suppose your literature professor hands out the following assignment in a class on the American novel: Write an analysis of some aspect of Mark Twain’s novel Huckleberry Finn. “This will be easy,” you think. “I loved Huckleberry Finn!” You grab a pad of paper and write:

Mark Twain’s Huckleberry Finn is a great American novel.

You begin to analyze your thesis:

• Do I answer the question? No. The prompt asks you to analyze some aspect of the novel. Your working thesis is a statement of general appreciation for the entire novel.

Think about aspects of the novel that are important to its structure or meaning—for example, the role of storytelling, the contrasting scenes between the shore and the river, or the relationships between adults and children. Now you write:

In Huckleberry Finn, Mark Twain develops a contrast between life on the river and life on the shore.

• Do I answer the question? Yes!
• Have I taken a position that others might challenge or oppose? Not really. This contrast is well-known and accepted.
• Is my thesis statement specific enough? It’s getting there–you have highlighted an important aspect of the novel for investigation. However, it’s still not clear what your analysis will reveal.
• Does my thesis pass the “how and why?” test? Not yet. Compare scenes from the book and see what you discover. Free write, make lists, jot down Huck’s actions and reactions and anything else that seems interesting.
• Does my thesis pass the “So what?” test? What’s the point of this contrast? What does it signify?”

After examining the evidence and considering your own insights, you write:

Through its contrasting river and shore scenes, Twain’s Huckleberry Finn suggests that to find the true expression of American democratic ideals, one must leave “civilized” society and go back to nature.

This final thesis statement presents an interpretation of a literary work based on an analysis of its content. Of course, for the essay itself to be successful, you must now present evidence from the novel that will convince the reader of your interpretation.

Works consulted

We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.

Anson, Chris M., and Robert A. Schwegler. 2010. The Longman Handbook for Writers and Readers , 6th ed. New York: Longman.

Lunsford, Andrea A. 2015. The St. Martin’s Handbook , 8th ed. Boston: Bedford/St Martin’s.

Ramage, John D., John C. Bean, and June Johnson. 2018. The Allyn & Bacon Guide to Writing , 8th ed. New York: Pearson.

Ruszkiewicz, John J., Christy Friend, Daniel Seward, and Maxine Hairston. 2010. The Scott, Foresman Handbook for Writers , 9th ed. Boston: Pearson Education.

You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill

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How Long is a Thesis or Dissertation: College, Grad or PhD

How long is a thesis

As a graduate student, you may have heard that you must complete a certain comprehensive project, either a thesis or a dissertation. In this guide, we will explore how long a thesis should be, the best length for a dissertation, and the optimal length for each part of the two.

If you read on to the end, we will also explore their differences to understand how it informs each length.

Both terms have distinct meanings, although they are sometimes used interchangeably and frequently confused.

Structure-wise, both papers have an introduction, a literature review, a body, a conclusion, a bibliography, and an appendix. That aside, both papers have some differences, as we shall see later on in this article.

How Long Should a Thesis be

Before discussing how long a thesis is, it’s critical to understand what it is. A thesis is a paper that marks the end of a study program.

Mostly, there is the undergraduate thesis, a project that marks the end of a bachelor’s degree, and a master’s thesis that marks the end of a master’s program.

A thesis should be around 50 pages long for a bachelor’s degree and 60-100 pages for a Master’s degree. However, the optimal length of a thesis project depends on the faculty’s instructions and the supervising professor’s expectations . The length also depends on the topic’s technicalities and the extent of research done.

A master’s thesis project is longer because it is a compilation of all your knowledge obtained in your master’s degree.

It basically allows you to demonstrate your abilities in your chosen field.

Often, graduate schools require students pursuing research-oriented degrees to write a thesis.

This is to demonstrate their practical skills before completing their degrees.

In contrast to undergraduate thesis, which are shorter in length and coverage area, usually less than 60 pages. A master’s theses are lengthy scholarly work allowing you to research a topic deeply.

Then you are required to write, expand the topic, and demonstrate what you have learned throughout the program. This is part of why you must write a thesis for some undergrad in some of the courses.

A Master’s thesis necessitates a large amount of research, which may include conducting interviews, surveys, and gathering information ( both primary and secondary) depending on the subject and field of study.

For this reason, the master’s thesis has between 60 and 100 pages, without including the bibliography. Mostly, the topic and research approach determine the length of the paper.

This means that there is no definite number of pages required. However, your thesis should be long enough to clearly and concisely present all important information.

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How long should a dissertation be.

A dissertation is a complex, in-depth research paper usually written by Ph.D. students. When writing the dissertation, Ph.D. Students are required to create their research, formulate a hypothesis, and conduct the study.

On average, a dissertation should be at least 90 pages at the minimum and 200 pages at the maximum , depending on the guidelines of the faculty and the professor. The optimal length for a dissertation also depends on the depth of the research done, the components of the file, and the level of study.

Most Ph.D. dissertations papers are between 120 to 200 pages on average.

However, as we said earlier, it all depends on factors like the field of study, and methods of data collection, among others.

Unlike a master’s thesis, which is about 100 pages, a dissertation is at least twice this length.

This is because you must develop a completely new concept, study it, research it, and defend it.

In your Ph.D. program, a dissertation allows you the opportunity to bring new knowledge, theories, or practices to your field of study.

The Lengths of Each Part of a Thesis and Dissertation

Factors Determining the Length of Thesis or Dissertation

As we have seen, there is no definite length of a thesis and dissertation. Most of these two important academic documents average 100 to 400 pages. However, several factors determine their length.

Universities- we all know universities are independent bodies. Also, it’s important to know that each university is different from the other. As a result, the thesis and dissertation length varies depending on the set rules in a certain college or school.

Field of study- some fields of study have rich information, while others have limited information.

For example, you may have much to write about or discover when it comes to science compared to history.

As such, if you are to write a thesis or a dissertation in both fields, one will definitely be longer than the other. Check the time it takes to write a thesis or a dissertation to get more points.

Other factors that affect the length of a thesis or a dissertation include your writing style and the instructor’s specifications. These factors also come into play when it comes to the time taken to defend a thesis or your dissertation.

Tips for the Optimal Length for a Thesis or Dissertation

Instead of writing for length, write for brevity. The goal is to write the smallest feasible document with all of the material needed to describe the study and back up the interpretation. Ensure to avoid irrelevant tangents and excessive repetitions at all costs.

The only repetition required is the main theme. The working hypothesis seeks to be elaborated and proved in your paper.

The theme is developed in the introduction, expanded in the body, and mentioned in the abstract and conclusion.

Here are some tips for writing the right length of thesis and dissertation:

• Remove any interpretation portion which is only tangentially linked to your new findings. 
• Use tables to keep track of information that is repeated.
• Include enough background information for the reader to understand the point of view.
• Make good use of figure captions.
• Let the table stand on its own. I.e., do not describe the contents of the figures and/or tables one by one in the text. Instead, highlight the most important patterns, objects, or trends in the figures and tables in the text.
• Leave out any observations or results in the text that you haven’t provided data.
• Do not include conclusions that aren’t backed up by your findings.
• Remove all inconclusive interpretation and discussion portions. 
• Avoid unnecessary adjectives, prepositional phrases, and adverbs.
• Make your sentences shorter – avoid nesting clauses or phrases.
• Avoid idioms and instead use words whose meaning can be looked up in a dictionary.

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Difference between a Thesis and a Dissertation

The most basic distinction between a thesis and a dissertation is when they are written.

While a thesis is a project completed after a master’s program, a dissertation is completed at the end of doctorate studies.

In a thesis, you present the results of your research to demonstrate that you have a thorough understanding of what you have studied during your master’s program.

On the other hand,  a dissertation is your chance to add new knowledge, theories, or practices to your field while pursuing a doctorate. The goal here is to come up with a completely new concept, develop it, and defend it.

A master’s thesis is similar to the types of research papers you’re used to writing in your bachelor’s studies. It involves conducting research on a topic, analyzing it, and then commenting on your findings and how it applies to your research topic.

The thesis aims to demonstrate your capacity to think critically about and explain a topic in depth.

Furthermore, with a thesis, you typically use this time to elaborate on a topic that is most relevant to your professional area of specialization that you intend to pursue.

In a dissertation, on the other hand, you use other people’s research as an inspiration to help you come up with and prove your own hypothesis, idea, or concept. The majority of the data in a dissertation is credited to you.

Last but not least, these two major works differ greatly in length. The average length of a master’s thesis is at least 100 pages.

On the other hand, a doctoral dissertation should be substantially longer because it includes a lot of history and research information, as well as every element of your research, while explaining how you arrived at the information.

It is a complex piece of scholarly work, and it is likely to be twice or thrice the length of a thesis. To know the difference, check the best length for a thesis paper and see more about it.

Here is a Recap of the Differences

• While the thesis is completed at the end of your master’s degree program, a dissertation is written at the end of your doctoral degree program.
• Both documents also vary in length. A thesis should have at least 100 pages, while a doctoral dissertation is longer (over 200 pages)
• In the thesis, you conduct original research; in the dissertation, you use existing research to help you develop your discovery.
• For a thesis, you have to add analysis to the existing work, while a dissertation is part of the analysis of the existing work.
• In comparison to a thesis, a dissertation requires a more thorough study to expand your research in a certain topic.
• The statements in a thesis and a dissertation are distinct. While a thesis statement explains to readers how you will prove an argument in your research, a dissertation hypothesis defines and clarifies the outcomes you expect from your study. Here, you apply a theory to explore a certain topic.
• A dissertation allows you to contribute new knowledge to your field of study, while a thesis makes sure you understand what you have studied in your program and how it applies.

A thesis or a dissertation is a difficult document to compile. However, you should not be worried since your school assigns you a dissertation advisor who is a faculty member.

These advisors or supervisors help you find resources and ensure that your proposal is on the right track when you get stuck.

Check out my guide on the differences between a research paper, proposal, and thesis to understand more about these issues.

Josh Jasen or JJ as we fondly call him, is a senior academic editor at Grade Bees in charge of the writing department. When not managing complex essays and academic writing tasks, Josh is busy advising students on how to pass assignments. In his spare time, he loves playing football or walking with his dog around the park.

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Master’s Thesis Length: How Long Should A Master’s Thesis Be?

Writing a thesis is one of the requirements for obtaining a master’s degree. If you are currently running a postgraduate program, you may be wondering what the actual length of a master’s thesis is.

A thesis is a comprehensive exploration of a topic or area of ​​interest. The idea is to chart your learning journey and conclude by discussing what you have learned and what others might learn from it, including opportunities for further research.

This article discusses the length and structure of a master’s thesis in detail.

What is a master’s thesis?

A master’s thesis is a research project written by students in a master’s degree program to demonstrate their interest and expertise in a specific topic within their field of study. It is the final requirement for a master’s degree.

Students are usually assigned an advisor who provides guidance and supervises their work. Once the thesis is complete, students must defend their work to a panel of two or more departmental faculty members.

How long is a master’s thesis?

Ultimately, the aim is to demonstrate your mastery in the field by demonstrating the academic expertise and research skills you have developed throughout the master’s program.

Master thesis structure

1. title page, 2. acknowledgment.

You should also thank your advisor, friends, and family who supported you during the course of your work.

3. Abstract

The aim of an abstract is to give the thesis committee a brief but concise insight into what your research work entails.

4. Table of contents

Additionally, you need to provide a list of figures and tables with the page number to find them in the thesis.

5. Introduction

6. literature review.

The literature review is the part of your thesis where you establish your arguments using various pre-existing scholarly publications and demonstrating your knowledge about your topic.

It is aimed to give a scientific overview of how your work contributes to existing knowledge on the subject matter. In other words, it shows readers the literature gap you hope to fill. For instance, your thesis may be based on new sets of data, methods, or applications.

7. Research methods

This chapter details the data used in your research and the method of gathering or collecting them. This could be qualitative data such as open-ended surveys, case studies, and more.

8. Data analysis and findings

Data analysis and finding involve experimenting with the gathered data and presenting your result in a graphical, tabular, or chart form. The result could also be a written description of the research and findings.

9. Discussion

This is the largest part of a thesis containing a series of chapters. The chapters should flow logically and build your arguments from one chapter to the next.

10. Conclusion

It should also include explaining whether your research questions are confirmed or rejected based on your research and comparing your findings with existing publications.

Not only that, the conclusion should state parts of your topic that you couldn’t touch. This helps buttress what your research has achieved and parts others can explore for future studies.

11. List of reference

12. statement of independent work, 13. appendix (or appendices).

The appendix is usually optional in a thesis. It is material that complements your argument. This could be a questionnaire or a case study.

If the content is too large to go into the body of your paper or could distract readers, then your research could use an appendix.

How to write a master’s thesis

A master’s thesis is longer than an undergraduate thesis, so, it would help if you start working on time to avoid rushing or late submission.

How fast can you write a master’s thesis?

Generally, students have two semesters to write their master’s thesis (usually the last two semesters of their degree program).

Can you finish your thesis in 3 weeks?

Can a master’s thesis be written in 20 pages.

20 pages may be too little to capture your arguments comprehensively in a master’s thesis. A typical master’s thesis has a length of about 50 pages and above.

Your work must also demonstrate great quality, so you want to give it your best shot. Perhaps you have a short time to complete your thesis, don’t fret. Simply think about how many words you need to write every day to meet up and develop plans to achieve your goal.

In all of this, you want to avoid plagiarism in your work, as this can have serious consequences. Read this article to know if paraphrasing is plagiarism.

I hope this article helped. Thanks for reading.

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Frequently asked questions

How long does it take to write a dissertation.

At the bachelor’s and master’s levels, the dissertation is usually the main focus of your final year. You might work on it (alongside other classes) for the entirety of the final year, or for the last six months. This includes formulating an idea, doing the research, and writing up.

A PhD thesis takes a longer time, as the thesis is the main focus of the degree. A PhD thesis might be being formulated and worked on for the whole four years of the degree program. The writing process alone can take around 18 months.

Frequently asked questions: Knowledge Base

Methodology refers to the overarching strategy and rationale of your research. Developing your methodology involves studying the research methods used in your field and the theories or principles that underpin them, in order to choose the approach that best matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. interviews, experiments , surveys , statistical tests ).

In a dissertation or scientific paper, the methodology chapter or methods section comes after the introduction and before the results , discussion and conclusion .

Depending on the length and type of document, you might also include a literature review or theoretical framework before the methodology.

Quantitative research deals with numbers and statistics, while qualitative research deals with words and meanings.

Quantitative methods allow you to test a hypothesis by systematically collecting and analysing data, while qualitative methods allow you to explore ideas and experiences in depth.

Reliability and validity are both about how well a method measures something:

• Reliability refers to the  consistency of a measure (whether the results can be reproduced under the same conditions).
• Validity   refers to the  accuracy of a measure (whether the results really do represent what they are supposed to measure).

If you are doing experimental research , you also have to consider the internal and external validity of your experiment.

A sample is a subset of individuals from a larger population. Sampling means selecting the group that you will actually collect data from in your research.

For example, if you are researching the opinions of students in your university, you could survey a sample of 100 students.

Statistical sampling allows you to test a hypothesis about the characteristics of a population. There are various sampling methods you can use to ensure that your sample is representative of the population as a whole.

There are several reasons to conduct a literature review at the beginning of a research project:

• To familiarise yourself with the current state of knowledge on your topic
• To ensure that you’re not just repeating what others have already done
• To identify gaps in knowledge and unresolved problems that your research can address
• To develop your theoretical framework and methodology
• To provide an overview of the key findings and debates on the topic

Writing the literature review shows your reader how your work relates to existing research and what new insights it will contribute.

A literature review is a survey of scholarly sources (such as books, journal articles, and theses) related to a specific topic or research question .

It is often written as part of a dissertation , thesis, research paper , or proposal .

The literature review usually comes near the beginning of your  dissertation . After the introduction , it grounds your research in a scholarly field and leads directly to your theoretical framework or methodology .

Harvard referencing uses an author–date system. Sources are cited by the author’s last name and the publication year in brackets. Each Harvard in-text citation corresponds to an entry in the alphabetised reference list at the end of the paper.

Vancouver referencing uses a numerical system. Sources are cited by a number in parentheses or superscript. Each number corresponds to a full reference at the end of the paper.

A Harvard in-text citation should appear in brackets every time you quote, paraphrase, or refer to information from a source.

The citation can appear immediately after the quotation or paraphrase, or at the end of the sentence. If you’re quoting, place the citation outside of the quotation marks but before any other punctuation like a comma or full stop.

In Harvard referencing, up to three author names are included in an in-text citation or reference list entry. When there are four or more authors, include only the first, followed by ‘ et al. ’

A bibliography should always contain every source you cited in your text. Sometimes a bibliography also contains other sources that you used in your research, but did not cite in the text.

MHRA doesn’t specify a rule about this, so check with your supervisor to find out exactly what should be included in your bibliography.

Footnote numbers should appear in superscript (e.g. 11 ). You can use the ‘Insert footnote’ button in Word to do this automatically; it’s in the ‘References’ tab at the top.

Footnotes always appear after the quote or paraphrase they relate to. MHRA generally recommends placing footnote numbers at the end of the sentence, immediately after any closing punctuation, like this. 12

In situations where this might be awkward or misleading, such as a long sentence containing multiple quotations, footnotes can also be placed at the end of a clause mid-sentence, like this; 13 note that they still come after any punctuation.

When a source has two or three authors, name all of them in your MHRA references . When there are four or more, use only the first name, followed by ‘and others’:

Note that in the bibliography, only the author listed first has their name inverted. The names of additional authors and those of translators or editors are written normally.

A citation should appear wherever you use information or ideas from a source, whether by quoting or paraphrasing its content.

In Vancouver style , you have some flexibility about where the citation number appears in the sentence – usually directly after mentioning the author’s name is best, but simply placing it at the end of the sentence is an acceptable alternative, as long as it’s clear what it relates to.

In Vancouver style , when you refer to a source with multiple authors in your text, you should only name the first author followed by ‘et al.’. This applies even when there are only two authors.

In your reference list, include up to six authors. For sources with seven or more authors, list the first six followed by ‘et al.’.

The words ‘ dissertation ’ and ‘thesis’ both refer to a large written research project undertaken to complete a degree, but they are used differently depending on the country:

• In the UK, you write a dissertation at the end of a bachelor’s or master’s degree, and you write a thesis to complete a PhD.
• In the US, it’s the other way around: you may write a thesis at the end of a bachelor’s or master’s degree, and you write a dissertation to complete a PhD.

The main difference is in terms of scale – a dissertation is usually much longer than the other essays you complete during your degree.

Another key difference is that you are given much more independence when working on a dissertation. You choose your own dissertation topic , and you have to conduct the research and write the dissertation yourself (with some assistance from your supervisor).

Dissertation word counts vary widely across different fields, institutions, and levels of education:

• An undergraduate dissertation is typically 8,000–15,000 words
• A master’s dissertation is typically 12,000–50,000 words
• A PhD thesis is typically book-length: 70,000–100,000 words

However, none of these are strict guidelines – your word count may be lower or higher than the numbers stated here. Always check the guidelines provided by your university to determine how long your own dissertation should be.

References should be included in your text whenever you use words, ideas, or information from a source. A source can be anything from a book or journal article to a website or YouTube video.

If you don’t acknowledge your sources, you can get in trouble for plagiarism .

Your university should tell you which referencing style to follow. If you’re unsure, check with a supervisor. Commonly used styles include:

• Harvard referencing , the most commonly used style in UK universities.
• MHRA , used in humanities subjects.
• APA , used in the social sciences.
• Vancouver , used in biomedicine.
• OSCOLA , used in law.

Your university may have its own referencing style guide.

If you are allowed to choose which style to follow, we recommend Harvard referencing, as it is a straightforward and widely used style.

To avoid plagiarism , always include a reference when you use words, ideas or information from a source. This shows that you are not trying to pass the work of others off as your own.

You must also properly quote or paraphrase the source. If you’re not sure whether you’ve done this correctly, you can use the Scribbr Plagiarism Checker to find and correct any mistakes.

In Harvard style , when you quote directly from a source that includes page numbers, your in-text citation must include a page number. For example: (Smith, 2014, p. 33).

You can also include page numbers to point the reader towards a passage that you paraphrased . If you refer to the general ideas or findings of the source as a whole, you don’t need to include a page number.

When you want to use a quote but can’t access the original source, you can cite it indirectly. In the in-text citation , first mention the source you want to refer to, and then the source in which you found it. For example:

It’s advisable to avoid indirect citations wherever possible, because they suggest you don’t have full knowledge of the sources you’re citing. Only use an indirect citation if you can’t reasonably gain access to the original source.

In Harvard style referencing , to distinguish between two sources by the same author that were published in the same year, you add a different letter after the year for each source:

• (Smith, 2019a)
• (Smith, 2019b)

Add ‘a’ to the first one you cite, ‘b’ to the second, and so on. Do the same in your bibliography or reference list .

To create a hanging indent for your bibliography or reference list :

• Highlight all the entries
• Click on the arrow in the bottom-right corner of the ‘Paragraph’ tab in the top menu.
• In the pop-up window, under ‘Special’ in the ‘Indentation’ section, use the drop-down menu to select ‘Hanging’.
• Then close the window with ‘OK’.

Though the terms are sometimes used interchangeably, there is a difference in meaning:

• A reference list only includes sources cited in the text – every entry corresponds to an in-text citation .
• A bibliography also includes other sources which were consulted during the research but not cited.

It’s important to assess the reliability of information found online. Look for sources from established publications and institutions with expertise (e.g. peer-reviewed journals and government agencies).

The CRAAP test (currency, relevance, authority, accuracy, purpose) can aid you in assessing sources, as can our list of credible sources . You should generally avoid citing websites like Wikipedia that can be edited by anyone – instead, look for the original source of the information in the “References” section.

You can generally omit page numbers in your in-text citations of online sources which don’t have them. But when you quote or paraphrase a specific passage from a particularly long online source, it’s useful to find an alternate location marker.

For text-based sources, you can use paragraph numbers (e.g. ‘para. 4’) or headings (e.g. ‘under “Methodology”’). With video or audio sources, use a timestamp (e.g. ‘10:15’).

In the acknowledgements of your thesis or dissertation, you should first thank those who helped you academically or professionally, such as your supervisor, funders, and other academics.

Then you can include personal thanks to friends, family members, or anyone else who supported you during the process.

Yes, it’s important to thank your supervisor(s) in the acknowledgements section of your thesis or dissertation .

Even if you feel your supervisor did not contribute greatly to the final product, you still should acknowledge them, if only for a very brief thank you. If you do not include your supervisor, it may be seen as a snub.

The acknowledgements are generally included at the very beginning of your thesis or dissertation, directly after the title page and before the abstract .

In a thesis or dissertation, the acknowledgements should usually be no longer than one page. There is no minimum length.

You may acknowledge God in your thesis or dissertation acknowledgements , but be sure to follow academic convention by also thanking the relevant members of academia, as well as family, colleagues, and friends who helped you.

All level 1 and 2 headings should be included in your table of contents . That means the titles of your chapters and the main sections within them.

The contents should also include all appendices and the lists of tables and figures, if applicable, as well as your reference list .

Do not include the acknowledgements or abstract   in the table of contents.

To automatically insert a table of contents in Microsoft Word, follow these steps:

• Apply heading styles throughout the document.
• In the references section in the ribbon, locate the Table of Contents group.
• Click the arrow next to the Table of Contents icon and select Custom Table of Contents.
• Select which levels of headings you would like to include in the table of contents.

Make sure to update your table of contents if you move text or change headings. To update, simply right click and select Update Field.

The table of contents in a thesis or dissertation always goes between your abstract and your introduction.

An abbreviation is a shortened version of an existing word, such as Dr for Doctor. In contrast, an acronym uses the first letter of each word to create a wholly new word, such as UNESCO (an acronym for the United Nations Educational, Scientific and Cultural Organization).

Your dissertation sometimes contains a list of abbreviations .

As a rule of thumb, write the explanation in full the first time you use an acronym or abbreviation. You can then proceed with the shortened version. However, if the abbreviation is very common (like UK or PC), then you can just use the abbreviated version straight away.

Be sure to add each abbreviation in your list of abbreviations !

If you only used a few abbreviations in your thesis or dissertation, you don’t necessarily need to include a list of abbreviations .

If your abbreviations are numerous, or if you think they won’t be known to your audience, it’s never a bad idea to add one. They can also improve readability, minimising confusion about abbreviations unfamiliar to your reader.

A list of abbreviations is a list of all the abbreviations you used in your thesis or dissertation. It should appear at the beginning of your document, immediately after your table of contents . It should always be in alphabetical order.

Fishbone diagrams have a few different names that are used interchangeably, including herringbone diagram, cause-and-effect diagram, and Ishikawa diagram.

These are all ways to refer to the same thing– a problem-solving approach that uses a fish-shaped diagram to model possible root causes of problems and troubleshoot solutions.

Fishbone diagrams (also called herringbone diagrams, cause-and-effect diagrams, and Ishikawa diagrams) are most popular in fields of quality management. They are also commonly used in nursing and healthcare, or as a brainstorming technique for students.

Some synonyms and near synonyms of among include:

• In the company of
• In the middle of
• Surrounded by

Some synonyms and near synonyms of between  include:

• In the space separating
• In the time separating

In spite of   is a preposition used to mean ‘ regardless of ‘, ‘notwithstanding’, or ‘even though’.

It’s always used in a subordinate clause to contrast with the information given in the main clause of a sentence (e.g., ‘Amy continued to watch TV, in spite of the time’).

Despite   is a preposition used to mean ‘ regardless of ‘, ‘notwithstanding’, or ‘even though’.

It’s used in a subordinate clause to contrast with information given in the main clause of a sentence (e.g., ‘Despite the stress, Joe loves his job’).

‘Log in’ is a phrasal verb meaning ‘connect to an electronic device, system, or app’. The preposition ‘to’ is often used directly after the verb; ‘in’ and ‘to’ should be written as two separate words (e.g., ‘ log in to the app to update privacy settings’).

‘Log into’ is sometimes used instead of ‘log in to’, but this is generally considered incorrect (as is ‘login to’).

Some synonyms and near synonyms of ensure include:

• Make certain

Some synonyms and near synonyms of assure  include:

Rest assured is an expression meaning ‘you can be certain’ (e.g., ‘Rest assured, I will find your cat’). ‘Assured’ is the adjectival form of the verb assure , meaning ‘convince’ or ‘persuade’.

Some synonyms and near synonyms for council include:

There are numerous synonyms and near synonyms for the two meanings of counsel :

AI writing tools can be used to perform a variety of tasks.

Generative AI writing tools (like ChatGPT ) generate text based on human inputs and can be used for interactive learning, to provide feedback, or to generate research questions or outlines.

These tools can also be used to paraphrase or summarise text or to identify grammar and punctuation mistakes. Y ou can also use Scribbr’s free paraphrasing tool , summarising tool , and grammar checker , which are designed specifically for these purposes.

Using AI writing tools (like ChatGPT ) to write your essay is usually considered plagiarism and may result in penalisation, unless it is allowed by your university. Text generated by AI tools is based on existing texts and therefore cannot provide unique insights. Furthermore, these outputs sometimes contain factual inaccuracies or grammar mistakes.

However, AI writing tools can be used effectively as a source of feedback and inspiration for your writing (e.g., to generate research questions ). Other AI tools, like grammar checkers, can help identify and eliminate grammar and punctuation mistakes to enhance your writing.

The Scribbr Knowledge Base is a collection of free resources to help you succeed in academic research, writing, and citation. Every week, we publish helpful step-by-step guides, clear examples, simple templates, engaging videos, and more.

The Knowledge Base is for students at all levels. Whether you’re writing your first essay, working on your bachelor’s or master’s dissertation, or getting to grips with your PhD research, we’ve got you covered.

As well as the Knowledge Base, Scribbr provides many other tools and services to support you in academic writing and citation:

• Create your citations and manage your reference list with our free Reference Generators in APA and MLA style.
• Scan your paper for in-text citation errors and inconsistencies with our innovative APA Citation Checker .
• Avoid accidental plagiarism with our reliable Plagiarism Checker .
• Polish your writing and get feedback on structure and clarity with our Proofreading & Editing services .

Yes! We’re happy for educators to use our content, and we’ve even adapted some of our articles into ready-made lecture slides .

You are free to display, distribute, and adapt Scribbr materials in your classes or upload them in private learning environments like Blackboard. We only ask that you credit Scribbr for any content you use.

We’re always striving to improve the Knowledge Base. If you have an idea for a topic we should cover, or you notice a mistake in any of our articles, let us know by emailing [email protected] .

The consequences of plagiarism vary depending on the type of plagiarism and the context in which it occurs. For example, submitting a whole paper by someone else will have the most severe consequences, while accidental citation errors are considered less serious.

If you’re a student, then you might fail the course, be suspended or expelled, or be obligated to attend a workshop on plagiarism. It depends on whether it’s your first offence or you’ve done it before.

As an academic or professional, plagiarising seriously damages your reputation. You might also lose your research funding or your job, and you could even face legal consequences for copyright infringement.

Paraphrasing without crediting the original author is a form of plagiarism , because you’re presenting someone else’s ideas as if they were your own.

However, paraphrasing is not plagiarism if you correctly reference the source . This means including an in-text referencing and a full reference , formatted according to your required citation style (e.g., Harvard , Vancouver ).

As well as referencing your source, make sure that any paraphrased text is completely rewritten in your own words.

Accidental plagiarism is one of the most common examples of plagiarism . Perhaps you forgot to cite a source, or paraphrased something a bit too closely. Maybe you can’t remember where you got an idea from, and aren’t totally sure if it’s original or not.

These all count as plagiarism, even though you didn’t do it on purpose. When in doubt, make sure you’re citing your sources . Also consider running your work through a plagiarism checker tool prior to submission, which work by using advanced database software to scan for matches between your text and existing texts.

Scribbr’s Plagiarism Checker takes less than 10 minutes and can help you turn in your paper with confidence.

The accuracy depends on the plagiarism checker you use. Per our in-depth research , Scribbr is the most accurate plagiarism checker. Many free plagiarism checkers fail to detect all plagiarism or falsely flag text as plagiarism.

Plagiarism checkers work by using advanced database software to scan for matches between your text and existing texts. Their accuracy is determined by two factors: the algorithm (which recognises the plagiarism) and the size of the database (with which your document is compared).

To avoid plagiarism when summarising an article or other source, follow these two rules:

• Write the summary entirely in your own words by   paraphrasing the author’s ideas.
• Reference the source with an in-text citation and a full reference so your reader can easily find the original text.

Plagiarism can be detected by your professor or readers if the tone, formatting, or style of your text is different in different parts of your paper, or if they’re familiar with the plagiarised source.

Many universities also use   plagiarism detection software like Turnitin’s, which compares your text to a large database of other sources, flagging any similarities that come up.

It can be easier than you think to commit plagiarism by accident. Consider using a   plagiarism checker prior to submitting your essay to ensure you haven’t missed any citations.

Some examples of plagiarism include:

• Copying and pasting a Wikipedia article into the body of an assignment
• Quoting a source without including a citation
• Not paraphrasing a source properly (e.g. maintaining wording too close to the original)
• Forgetting to cite the source of an idea

The most surefire way to   avoid plagiarism is to always cite your sources . When in doubt, cite!

Global plagiarism means taking an entire work written by someone else and passing it off as your own. This can include getting someone else to write an essay or assignment for you, or submitting a text you found online as your own work.

Global plagiarism is one of the most serious types of plagiarism because it involves deliberately and directly lying about the authorship of a work. It can have severe consequences for students and professionals alike.

Verbatim plagiarism means copying text from a source and pasting it directly into your own document without giving proper credit.

If the structure and the majority of the words are the same as in the original source, then you are committing verbatim plagiarism. This is the case even if you delete a few words or replace them with synonyms.

If you want to use an author’s exact words, you need to quote the original source by putting the copied text in quotation marks and including an   in-text citation .

Patchwork plagiarism , also called mosaic plagiarism, means copying phrases, passages, or ideas from various existing sources and combining them to create a new text. This includes slightly rephrasing some of the content, while keeping many of the same words and the same structure as the original.

While this type of plagiarism is more insidious than simply copying and pasting directly from a source, plagiarism checkers like Turnitin’s can still easily detect it.

To avoid plagiarism in any form, remember to reference your sources .

Yes, reusing your own work without citation is considered self-plagiarism . This can range from resubmitting an entire assignment to reusing passages or data from something you’ve handed in previously.

Self-plagiarism often has the same consequences as other types of plagiarism . If you want to reuse content you wrote in the past, make sure to check your university’s policy or consult your professor.

If you are reusing content or data you used in a previous assignment, make sure to cite yourself. You can cite yourself the same way you would cite any other source: simply follow the directions for the citation style you are using.

Keep in mind that reusing prior content can be considered self-plagiarism , so make sure you ask your instructor or consult your university’s handbook prior to doing so.

Most institutions have an internal database of previously submitted student assignments. Turnitin can check for self-plagiarism by comparing your paper against this database. If you’ve reused parts of an assignment you already submitted, it will flag any similarities as potential plagiarism.

Online plagiarism checkers don’t have access to your institution’s database, so they can’t detect self-plagiarism of unpublished work. If you’re worried about accidentally self-plagiarising, you can use Scribbr’s Self-Plagiarism Checker to upload your unpublished documents and check them for similarities.

Plagiarism has serious consequences and can be illegal in certain scenarios.

While most of the time plagiarism in an undergraduate setting is not illegal, plagiarism or self-plagiarism in a professional academic setting can lead to legal action, including copyright infringement and fraud. Many scholarly journals do not allow you to submit the same work to more than one journal, and if you do not credit a coauthor, you could be legally defrauding them.

Even if you aren’t breaking the law, plagiarism can seriously impact your academic career. While the exact consequences of plagiarism vary by institution and severity, common consequences include a lower grade, automatically failing a course, academic suspension or probation, and even expulsion.

Self-plagiarism means recycling work that you’ve previously published or submitted as an assignment. It’s considered academic dishonesty to present something as brand new when you’ve already gotten credit and perhaps feedback for it in the past.

If you want to refer to ideas or data from previous work, be sure to cite yourself.

Academic integrity means being honest, ethical, and thorough in your academic work. To maintain academic integrity, you should avoid misleading your readers about any part of your research and refrain from offences like plagiarism and contract cheating, which are examples of academic misconduct.

Academic dishonesty refers to deceitful or misleading behavior in an academic setting. Academic dishonesty can occur intentionally or unintentionally, and it varies in severity.

It can encompass paying for a pre-written essay, cheating on an exam, or committing plagiarism . It can also include helping others cheat, copying a friend’s homework answers, or even pretending to be sick to miss an exam.

Academic dishonesty doesn’t just occur in a classroom setting, but also in research and other academic-adjacent fields.

Consequences of academic dishonesty depend on the severity of the offence and your institution’s policy. They can range from a warning for a first offence to a failing grade in a course to expulsion from your university.

For those in certain fields, such as nursing, engineering, or lab sciences, not learning fundamentals properly can directly impact the health and safety of others. For those working in academia or research, academic dishonesty impacts your professional reputation, leading others to doubt your future work.

Academic dishonesty can be intentional or unintentional, ranging from something as simple as claiming to have read something you didn’t to copying your neighbour’s answers on an exam.

You can commit academic dishonesty with the best of intentions, such as helping a friend cheat on a paper. Severe academic dishonesty can include buying a pre-written essay or the answers to a multiple-choice test, or falsifying a medical emergency to avoid taking a final exam.

Plagiarism means presenting someone else’s work as your own without giving proper credit to the original author. In academic writing, plagiarism involves using words, ideas, or information from a source without including a citation .

Plagiarism can have serious consequences , even when it’s done accidentally. To avoid plagiarism, it’s important to keep track of your sources and cite them correctly.

Common knowledge does not need to be cited. However, you should be extra careful when deciding what counts as common knowledge.

Common knowledge encompasses information that the average educated reader would accept as true without needing the extra validation of a source or citation.

Common knowledge should be widely known, undisputed, and easily verified. When in doubt, always cite your sources.

Most online plagiarism checkers only have access to public databases, whose software doesn’t allow you to compare two documents for plagiarism.

However, in addition to our Plagiarism Checker , Scribbr also offers an Self-Plagiarism Checker . This is an add-on tool that lets you compare your paper with unpublished or private documents. This way you can rest assured that you haven’t unintentionally plagiarised or self-plagiarised .

Compare two sources for plagiarism

The research methods you use depend on the type of data you need to answer your research question .

• If you want to measure something or test a hypothesis , use quantitative methods . If you want to explore ideas, thoughts, and meanings, use qualitative methods .
• If you want to analyse a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how they are generated, collect primary data.
• If you want to establish cause-and-effect relationships between variables , use experimental methods. If you want to understand the characteristics of a research subject, use descriptive methods.

Methodology refers to the overarching strategy and rationale of your research project . It involves studying the methods used in your field and the theories or principles behind them, in order to develop an approach that matches your objectives.

Methods are the specific tools and procedures you use to collect and analyse data (e.g. experiments, surveys , and statistical tests ).

In shorter scientific papers, where the aim is to report the findings of a specific study, you might simply describe what you did in a methods section .

In a longer or more complex research project, such as a thesis or dissertation , you will probably include a methodology section , where you explain your approach to answering the research questions and cite relevant sources to support your choice of methods.

In mixed methods research , you use both qualitative and quantitative data collection and analysis methods to answer your research question .

Data collection is the systematic process by which observations or measurements are gathered in research. It is used in many different contexts by academics, governments, businesses, and other organisations.

There are various approaches to qualitative data analysis , but they all share five steps in common:

• Prepare and organise your data.
• Review and explore your data.
• Develop a data coding system.
• Assign codes to the data.
• Identify recurring themes.

The specifics of each step depend on the focus of the analysis. Some common approaches include textual analysis , thematic analysis , and discourse analysis .

There are five common approaches to qualitative research :

• Grounded theory involves collecting data in order to develop new theories.
• Ethnography involves immersing yourself in a group or organisation to understand its culture.
• Narrative research involves interpreting stories to understand how people make sense of their experiences and perceptions.
• Phenomenological research involves investigating phenomena through people’s lived experiences.
• Action research links theory and practice in several cycles to drive innovative changes.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics. It is used by scientists to test specific predictions, called hypotheses , by calculating how likely it is that a pattern or relationship between variables could have arisen by chance.

Operationalisation means turning abstract conceptual ideas into measurable observations.

For example, the concept of social anxiety isn’t directly observable, but it can be operationally defined in terms of self-rating scores, behavioural avoidance of crowded places, or physical anxiety symptoms in social situations.

Before collecting data , it’s important to consider how you will operationalise the variables that you want to measure.

Triangulation in research means using multiple datasets, methods, theories and/or investigators to address a research question. It’s a research strategy that can help you enhance the validity and credibility of your findings.

Triangulation is mainly used in qualitative research , but it’s also commonly applied in quantitative research . Mixed methods research always uses triangulation.

These are four of the most common mixed methods designs :

• Convergent parallel: Quantitative and qualitative data are collected at the same time and analysed separately. After both analyses are complete, compare your results to draw overall conclusions. 
• Embedded: Quantitative and qualitative data are collected at the same time, but within a larger quantitative or qualitative design. One type of data is secondary to the other.
• Explanatory sequential: Quantitative data is collected and analysed first, followed by qualitative data. You can use this design if you think your qualitative data will explain and contextualise your quantitative findings.
• Exploratory sequential: Qualitative data is collected and analysed first, followed by quantitative data. You can use this design if you think the quantitative data will confirm or validate your qualitative findings.

An observational study could be a good fit for your research if your research question is based on things you observe. If you have ethical, logistical, or practical concerns that make an experimental design challenging, consider an observational study. Remember that in an observational study, it is critical that there be no interference or manipulation of the research subjects. Since it’s not an experiment, there are no control or treatment groups either.

The key difference between observational studies and experiments is that, done correctly, an observational study will never influence the responses or behaviours of participants. Experimental designs will have a treatment condition applied to at least a portion of participants.

Exploratory research explores the main aspects of a new or barely researched question.

Explanatory research explains the causes and effects of an already widely researched question.

Experimental designs are a set of procedures that you plan in order to examine the relationship between variables that interest you.

To design a successful experiment, first identify:

• A testable hypothesis
• One or more independent variables that you will manipulate
• One or more dependent variables that you will measure

When designing the experiment, first decide:

• How your variable(s) will be manipulated
• How you will control for any potential confounding or lurking variables
• How many subjects you will include
• How you will assign treatments to your subjects

There are four main types of triangulation :

• Data triangulation : Using data from different times, spaces, and people
• Investigator triangulation : Involving multiple researchers in collecting or analysing data
• Theory triangulation : Using varying theoretical perspectives in your research
• Methodological triangulation : Using different methodologies to approach the same topic

Triangulation can help:

• Reduce bias that comes from using a single method, theory, or investigator
• Enhance validity by approaching the same topic with different tools
• Establish credibility by giving you a complete picture of the research problem

But triangulation can also pose problems:

• It’s time-consuming and labour-intensive, often involving an interdisciplinary team.
• Your results may be inconsistent or even contradictory.

A confounding variable , also called a confounder or confounding factor, is a third variable in a study examining a potential cause-and-effect relationship.

A confounding variable is related to both the supposed cause and the supposed effect of the study. It can be difficult to separate the true effect of the independent variable from the effect of the confounding variable.

In your research design , it’s important to identify potential confounding variables and plan how you will reduce their impact.

In a between-subjects design , every participant experiences only one condition, and researchers assess group differences between participants in various conditions.

In a within-subjects design , each participant experiences all conditions, and researchers test the same participants repeatedly for differences between conditions.

The word ‘between’ means that you’re comparing different conditions between groups, while the word ‘within’ means you’re comparing different conditions within the same group.

A quasi-experiment is a type of research design that attempts to establish a cause-and-effect relationship. The main difference between this and a true experiment is that the groups are not randomly assigned.

In experimental research, random assignment is a way of placing participants from your sample into different groups using randomisation. With this method, every member of the sample has a known or equal chance of being placed in a control group or an experimental group.

Quasi-experimental design is most useful in situations where it would be unethical or impractical to run a true experiment .

Quasi-experiments have lower internal validity than true experiments, but they often have higher external validity  as they can use real-world interventions instead of artificial laboratory settings.

Within-subjects designs have many potential threats to internal validity , but they are also very statistically powerful .

Advantages:

• Only requires small samples
• Statistically powerful
• Removes the effects of individual differences on the outcomes

Disadvantages:

• Internal validity threats reduce the likelihood of establishing a direct relationship between variables
• Time-related effects, such as growth, can influence the outcomes
• Carryover effects mean that the specific order of different treatments affect the outcomes

Yes. Between-subjects and within-subjects designs can be combined in a single study when you have two or more independent variables (a factorial design). In a mixed factorial design, one variable is altered between subjects and another is altered within subjects.

In a factorial design, multiple independent variables are tested.

If you test two variables, each level of one independent variable is combined with each level of the other independent variable to create different conditions.

While a between-subjects design has fewer threats to internal validity , it also requires more participants for high statistical power than a within-subjects design .

• Prevents carryover effects of learning and fatigue.
• Shorter study duration.
• Needs larger samples for high power.
• Uses more resources to recruit participants, administer sessions, cover costs, etc.
• Individual differences may be an alternative explanation for results.

Samples are used to make inferences about populations . Samples are easier to collect data from because they are practical, cost-effective, convenient, and manageable.

Probability sampling means that every member of the target population has a known chance of being included in the sample.

Probability sampling methods include simple random sampling , systematic sampling , stratified sampling , and cluster sampling .

In non-probability sampling , the sample is selected based on non-random criteria, and not every member of the population has a chance of being included.

Common non-probability sampling methods include convenience sampling , voluntary response sampling, purposive sampling , snowball sampling , and quota sampling .

In multistage sampling , or multistage cluster sampling, you draw a sample from a population using smaller and smaller groups at each stage.

This method is often used to collect data from a large, geographically spread group of people in national surveys, for example. You take advantage of hierarchical groupings (e.g., from county to city to neighbourhood) to create a sample that’s less expensive and time-consuming to collect data from.

Sampling bias occurs when some members of a population are systematically more likely to be selected in a sample than others.

Simple random sampling is a type of probability sampling in which the researcher randomly selects a subset of participants from a population . Each member of the population has an equal chance of being selected. Data are then collected from as large a percentage as possible of this random subset.

The American Community Survey  is an example of simple random sampling . In order to collect detailed data on the population of the US, the Census Bureau officials randomly select 3.5 million households per year and use a variety of methods to convince them to fill out the survey.

If properly implemented, simple random sampling is usually the best sampling method for ensuring both internal and external validity . However, it can sometimes be impractical and expensive to implement, depending on the size of the population to be studied,

If you have a list of every member of the population and the ability to reach whichever members are selected, you can use simple random sampling.

Cluster sampling is more time- and cost-efficient than other probability sampling methods , particularly when it comes to large samples spread across a wide geographical area.

However, it provides less statistical certainty than other methods, such as simple random sampling , because it is difficult to ensure that your clusters properly represent the population as a whole.

There are three types of cluster sampling : single-stage, double-stage and multi-stage clustering. In all three types, you first divide the population into clusters, then randomly select clusters for use in your sample.

• In single-stage sampling , you collect data from every unit within the selected clusters.
• In double-stage sampling , you select a random sample of units from within the clusters.
• In multi-stage sampling , you repeat the procedure of randomly sampling elements from within the clusters until you have reached a manageable sample.

Cluster sampling is a probability sampling method in which you divide a population into clusters, such as districts or schools, and then randomly select some of these clusters as your sample.

The clusters should ideally each be mini-representations of the population as a whole.

In multistage sampling , you can use probability or non-probability sampling methods.

For a probability sample, you have to probability sampling at every stage. You can mix it up by using simple random sampling , systematic sampling , or stratified sampling to select units at different stages, depending on what is applicable and relevant to your study.

Multistage sampling can simplify data collection when you have large, geographically spread samples, and you can obtain a probability sample without a complete sampling frame.

But multistage sampling may not lead to a representative sample, and larger samples are needed for multistage samples to achieve the statistical properties of simple random samples .

In stratified sampling , researchers divide subjects into subgroups called strata based on characteristics that they share (e.g., race, gender, educational attainment).

Once divided, each subgroup is randomly sampled using another probability sampling method .

You should use stratified sampling when your sample can be divided into mutually exclusive and exhaustive subgroups that you believe will take on different mean values for the variable that you’re studying.

Using stratified sampling will allow you to obtain more precise (with lower variance ) statistical estimates of whatever you are trying to measure.

For example, say you want to investigate how income differs based on educational attainment, but you know that this relationship can vary based on race. Using stratified sampling, you can ensure you obtain a large enough sample from each racial group, allowing you to draw more precise conclusions.

Yes, you can create a stratified sample using multiple characteristics, but you must ensure that every participant in your study belongs to one and only one subgroup. In this case, you multiply the numbers of subgroups for each characteristic to get the total number of groups.

For example, if you were stratifying by location with three subgroups (urban, rural, or suburban) and marital status with five subgroups (single, divorced, widowed, married, or partnered), you would have 3 × 5 = 15 subgroups.

There are three key steps in systematic sampling :

• Define and list your population , ensuring that it is not ordered in a cyclical or periodic order.
• Decide on your sample size and calculate your interval, k , by dividing your population by your target sample size.
• Choose every k th member of the population as your sample.

Systematic sampling is a probability sampling method where researchers select members of the population at a regular interval – for example, by selecting every 15th person on a list of the population. If the population is in a random order, this can imitate the benefits of simple random sampling .

Populations are used when a research question requires data from every member of the population. This is usually only feasible when the population is small and easily accessible.

A statistic refers to measures about the sample , while a parameter refers to measures about the population .

A sampling error is the difference between a population parameter and a sample statistic .

There are eight threats to internal validity : history, maturation, instrumentation, testing, selection bias , regression to the mean, social interaction, and attrition .

Internal validity is the extent to which you can be confident that a cause-and-effect relationship established in a study cannot be explained by other factors.

Attrition bias is a threat to internal validity . In experiments, differential rates of attrition between treatment and control groups can skew results.

This bias can affect the relationship between your independent and dependent variables . It can make variables appear to be correlated when they are not, or vice versa.

The external validity of a study is the extent to which you can generalise your findings to different groups of people, situations, and measures.

The two types of external validity are population validity (whether you can generalise to other groups of people) and ecological validity (whether you can generalise to other situations and settings).

There are seven threats to external validity : selection bias , history, experimenter effect, Hawthorne effect , testing effect, aptitude-treatment, and situation effect.

Attrition bias can skew your sample so that your final sample differs significantly from your original sample. Your sample is biased because some groups from your population are underrepresented.

With a biased final sample, you may not be able to generalise your findings to the original population that you sampled from, so your external validity is compromised.

Construct validity is about how well a test measures the concept it was designed to evaluate. It’s one of four types of measurement validity , which includes construct validity, face validity , and criterion validity.

There are two subtypes of construct validity.

• Convergent validity : The extent to which your measure corresponds to measures of related constructs
• Discriminant validity: The extent to which your measure is unrelated or negatively related to measures of distinct constructs

When designing or evaluating a measure, construct validity helps you ensure you’re actually measuring the construct you’re interested in. If you don’t have construct validity, you may inadvertently measure unrelated or distinct constructs and lose precision in your research.

Construct validity is often considered the overarching type of measurement validity ,  because it covers all of the other types. You need to have face validity , content validity, and criterion validity to achieve construct validity.

Statistical analyses are often applied to test validity with data from your measures. You test convergent validity and discriminant validity with correlations to see if results from your test are positively or negatively related to those of other established tests.

You can also use regression analyses to assess whether your measure is actually predictive of outcomes that you expect it to predict theoretically. A regression analysis that supports your expectations strengthens your claim of construct validity .

Face validity is about whether a test appears to measure what it’s supposed to measure. This type of validity is concerned with whether a measure seems relevant and appropriate for what it’s assessing only on the surface.

Face validity is important because it’s a simple first step to measuring the overall validity of a test or technique. It’s a relatively intuitive, quick, and easy way to start checking whether a new measure seems useful at first glance.

Good face validity means that anyone who reviews your measure says that it seems to be measuring what it’s supposed to. With poor face validity, someone reviewing your measure may be left confused about what you’re measuring and why you’re using this method.

It’s often best to ask a variety of people to review your measurements. You can ask experts, such as other researchers, or laypeople, such as potential participants, to judge the face validity of tests.

While experts have a deep understanding of research methods , the people you’re studying can provide you with valuable insights you may have missed otherwise.

There are many different types of inductive reasoning that people use formally or informally.

Here are a few common types:

• Inductive generalisation : You use observations about a sample to come to a conclusion about the population it came from.
• Statistical generalisation: You use specific numbers about samples to make statements about populations.
• Causal reasoning: You make cause-and-effect links between different things.
• Sign reasoning: You make a conclusion about a correlational relationship between different things.
• Analogical reasoning: You make a conclusion about something based on its similarities to something else.

Inductive reasoning is a bottom-up approach, while deductive reasoning is top-down.

Inductive reasoning takes you from the specific to the general, while in deductive reasoning, you make inferences by going from general premises to specific conclusions.

In inductive research , you start by making observations or gathering data. Then, you take a broad scan of your data and search for patterns. Finally, you make general conclusions that you might incorporate into theories.

Inductive reasoning is a method of drawing conclusions by going from the specific to the general. It’s usually contrasted with deductive reasoning, where you proceed from general information to specific conclusions.

Inductive reasoning is also called inductive logic or bottom-up reasoning.

Deductive reasoning is a logical approach where you progress from general ideas to specific conclusions. It’s often contrasted with inductive reasoning , where you start with specific observations and form general conclusions.

Deductive reasoning is also called deductive logic.

Deductive reasoning is commonly used in scientific research, and it’s especially associated with quantitative research .

In research, you might have come across something called the hypothetico-deductive method . It’s the scientific method of testing hypotheses to check whether your predictions are substantiated by real-world data.

A dependent variable is what changes as a result of the independent variable manipulation in experiments . It’s what you’re interested in measuring, and it ‘depends’ on your independent variable.

In statistics, dependent variables are also called:

• Response variables (they respond to a change in another variable)
• Outcome variables (they represent the outcome you want to measure)
• Left-hand-side variables (they appear on the left-hand side of a regression equation)

An independent variable is the variable you manipulate, control, or vary in an experimental study to explore its effects. It’s called ‘independent’ because it’s not influenced by any other variables in the study.

Independent variables are also called:

• Explanatory variables (they explain an event or outcome)
• Predictor variables (they can be used to predict the value of a dependent variable)
• Right-hand-side variables (they appear on the right-hand side of a regression equation)

A correlation is usually tested for two variables at a time, but you can test correlations between three or more variables.

On graphs, the explanatory variable is conventionally placed on the x -axis, while the response variable is placed on the y -axis.

• If you have quantitative variables , use a scatterplot or a line graph.
• If your response variable is categorical, use a scatterplot or a line graph.
• If your explanatory variable is categorical, use a bar graph.

The term ‘ explanatory variable ‘ is sometimes preferred over ‘ independent variable ‘ because, in real-world contexts, independent variables are often influenced by other variables. This means they aren’t totally independent.

Multiple independent variables may also be correlated with each other, so ‘explanatory variables’ is a more appropriate term.

The difference between explanatory and response variables is simple:

• An explanatory variable is the expected cause, and it explains the results.
• A response variable is the expected effect, and it responds to other variables.

There are 4 main types of extraneous variables :

• Demand characteristics : Environmental cues that encourage participants to conform to researchers’ expectations
• Experimenter effects : Unintentional actions by researchers that influence study outcomes
• Situational variables : Eenvironmental variables that alter participants’ behaviours
• Participant variables : Any characteristic or aspect of a participant’s background that could affect study results

An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study.

A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.

‘Controlling for a variable’ means measuring extraneous variables and accounting for them statistically to remove their effects on other variables.

Researchers often model control variable data along with independent and dependent variable data in regression analyses and ANCOVAs . That way, you can isolate the control variable’s effects from the relationship between the variables of interest.

Control variables help you establish a correlational or causal relationship between variables by enhancing internal validity .

If you don’t control relevant extraneous variables , they may influence the outcomes of your study, and you may not be able to demonstrate that your results are really an effect of your independent variable .

A control variable is any variable that’s held constant in a research study. It’s not a variable of interest in the study, but it’s controlled because it could influence the outcomes.

In statistics, ordinal and nominal variables are both considered categorical variables .

Even though ordinal data can sometimes be numerical, not all mathematical operations can be performed on them.

In scientific research, concepts are the abstract ideas or phenomena that are being studied (e.g., educational achievement). Variables are properties or characteristics of the concept (e.g., performance at school), while indicators are ways of measuring or quantifying variables (e.g., yearly grade reports).

The process of turning abstract concepts into measurable variables and indicators is called operationalisation .

There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control, and randomisation.

In restriction , you restrict your sample by only including certain subjects that have the same values of potential confounding variables.

In matching , you match each of the subjects in your treatment group with a counterpart in the comparison group. The matched subjects have the same values on any potential confounding variables, and only differ in the independent variable .

In statistical control , you include potential confounders as variables in your regression .

In randomisation , you randomly assign the treatment (or independent variable) in your study to a sufficiently large number of subjects, which allows you to control for all potential confounding variables.

A confounding variable is closely related to both the independent and dependent variables in a study. An independent variable represents the supposed cause , while the dependent variable is the supposed effect . A confounding variable is a third variable that influences both the independent and dependent variables.

Failing to account for confounding variables can cause you to wrongly estimate the relationship between your independent and dependent variables.

To ensure the internal validity of your research, you must consider the impact of confounding variables. If you fail to account for them, you might over- or underestimate the causal relationship between your independent and dependent variables , or even find a causal relationship where none exists.

Yes, but including more than one of either type requires multiple research questions .

For example, if you are interested in the effect of a diet on health, you can use multiple measures of health: blood sugar, blood pressure, weight, pulse, and many more. Each of these is its own dependent variable with its own research question.

You could also choose to look at the effect of exercise levels as well as diet, or even the additional effect of the two combined. Each of these is a separate independent variable .

To ensure the internal validity of an experiment , you should only change one independent variable at a time.

No. The value of a dependent variable depends on an independent variable, so a variable cannot be both independent and dependent at the same time. It must be either the cause or the effect, not both.

You want to find out how blood sugar levels are affected by drinking diet cola and regular cola, so you conduct an experiment .

• The type of cola – diet or regular – is the independent variable .
• The level of blood sugar that you measure is the dependent variable – it changes depending on the type of cola.

Determining cause and effect is one of the most important parts of scientific research. It’s essential to know which is the cause – the independent variable – and which is the effect – the dependent variable.

Quantitative variables are any variables where the data represent amounts (e.g. height, weight, or age).

Categorical variables are any variables where the data represent groups. This includes rankings (e.g. finishing places in a race), classifications (e.g. brands of cereal), and binary outcomes (e.g. coin flips).

You need to know what type of variables you are working with to choose the right statistical test for your data and interpret your results .

Discrete and continuous variables are two types of quantitative variables :

• Discrete variables represent counts (e.g., the number of objects in a collection).
• Continuous variables represent measurable amounts (e.g., water volume or weight).

You can think of independent and dependent variables in terms of cause and effect: an independent variable is the variable you think is the cause , while a dependent variable is the effect .

In an experiment, you manipulate the independent variable and measure the outcome in the dependent variable. For example, in an experiment about the effect of nutrients on crop growth:

• The  independent variable  is the amount of nutrients added to the crop field.
• The  dependent variable is the biomass of the crops at harvest time.

Defining your variables, and deciding how you will manipulate and measure them, is an important part of experimental design .

Including mediators and moderators in your research helps you go beyond studying a simple relationship between two variables for a fuller picture of the real world. They are important to consider when studying complex correlational or causal relationships.

Mediators are part of the causal pathway of an effect, and they tell you how or why an effect takes place. Moderators usually help you judge the external validity of your study by identifying the limitations of when the relationship between variables holds.

If something is a mediating variable :

• It’s caused by the independent variable
• It influences the dependent variable
• When it’s taken into account, the statistical correlation between the independent and dependent variables is higher than when it isn’t considered

A confounder is a third variable that affects variables of interest and makes them seem related when they are not. In contrast, a mediator is the mechanism of a relationship between two variables: it explains the process by which they are related.

A mediator variable explains the process through which two variables are related, while a moderator variable affects the strength and direction of that relationship.

When conducting research, collecting original data has significant advantages:

• You can tailor data collection to your specific research aims (e.g., understanding the needs of your consumers or user testing your website).
• You can control and standardise the process for high reliability and validity (e.g., choosing appropriate measurements and sampling methods ).

However, there are also some drawbacks: data collection can be time-consuming, labour-intensive, and expensive. In some cases, it’s more efficient to use secondary data that has already been collected by someone else, but the data might be less reliable.

A structured interview is a data collection method that relies on asking questions in a set order to collect data on a topic. They are often quantitative in nature. Structured interviews are best used when:

• You already have a very clear understanding of your topic. Perhaps significant research has already been conducted, or you have done some prior research yourself, but you already possess a baseline for designing strong structured questions.
• You are constrained in terms of time or resources and need to analyse your data quickly and efficiently
• Your research question depends on strong parity between participants, with environmental conditions held constant

More flexible interview options include semi-structured interviews , unstructured interviews , and focus groups .

The interviewer effect is a type of bias that emerges when a characteristic of an interviewer (race, age, gender identity, etc.) influences the responses given by the interviewee.

There is a risk of an interviewer effect in all types of interviews , but it can be mitigated by writing really high-quality interview questions.

A semi-structured interview is a blend of structured and unstructured types of interviews. Semi-structured interviews are best used when:

• You have prior interview experience. Spontaneous questions are deceptively challenging, and it’s easy to accidentally ask a leading question or make a participant uncomfortable.
• Your research question is exploratory in nature. Participant answers can guide future research questions and help you develop a more robust knowledge base for future research.

An unstructured interview is the most flexible type of interview, but it is not always the best fit for your research topic.

Unstructured interviews are best used when:

• You are an experienced interviewer and have a very strong background in your research topic, since it is challenging to ask spontaneous, colloquial questions
• Your research question is exploratory in nature. While you may have developed hypotheses, you are open to discovering new or shifting viewpoints through the interview process.
• You are seeking descriptive data, and are ready to ask questions that will deepen and contextualise your initial thoughts and hypotheses
• Your research depends on forming connections with your participants and making them feel comfortable revealing deeper emotions, lived experiences, or thoughts

The four most common types of interviews are:

• Structured interviews : The questions are predetermined in both topic and order.
• Semi-structured interviews : A few questions are predetermined, but other questions aren’t planned.
• Unstructured interviews : None of the questions are predetermined.
• Focus group interviews : The questions are presented to a group instead of one individual.

A focus group is a research method that brings together a small group of people to answer questions in a moderated setting. The group is chosen due to predefined demographic traits, and the questions are designed to shed light on a topic of interest. It is one of four types of interviews .

Social desirability bias is the tendency for interview participants to give responses that will be viewed favourably by the interviewer or other participants. It occurs in all types of interviews and surveys , but is most common in semi-structured interviews , unstructured interviews , and focus groups .

Social desirability bias can be mitigated by ensuring participants feel at ease and comfortable sharing their views. Make sure to pay attention to your own body language and any physical or verbal cues, such as nodding or widening your eyes.

This type of bias in research can also occur in observations if the participants know they’re being observed. They might alter their behaviour accordingly.

As a rule of thumb, questions related to thoughts, beliefs, and feelings work well in focus groups . Take your time formulating strong questions, paying special attention to phrasing. Be careful to avoid leading questions , which can bias your responses.

Overall, your focus group questions should be:

• Open-ended and flexible
• Impossible to answer with ‘yes’ or ‘no’ (questions that start with ‘why’ or ‘how’ are often best)
• Unambiguous, getting straight to the point while still stimulating discussion
• Unbiased and neutral

The third variable and directionality problems are two main reasons why correlation isn’t causation .

The third variable problem means that a confounding variable affects both variables to make them seem causally related when they are not.

The directionality problem is when two variables correlate and might actually have a causal relationship, but it’s impossible to conclude which variable causes changes in the other.

Controlled experiments establish causality, whereas correlational studies only show associations between variables.

• In an experimental design , you manipulate an independent variable and measure its effect on a dependent variable. Other variables are controlled so they can’t impact the results.
• In a correlational design , you measure variables without manipulating any of them. You can test whether your variables change together, but you can’t be sure that one variable caused a change in another.

In general, correlational research is high in external validity while experimental research is high in internal validity .

A correlation coefficient is a single number that describes the strength and direction of the relationship between your variables.

Different types of correlation coefficients might be appropriate for your data based on their levels of measurement and distributions . The Pearson product-moment correlation coefficient (Pearson’s r ) is commonly used to assess a linear relationship between two quantitative variables.

A correlational research design investigates relationships between two variables (or more) without the researcher controlling or manipulating any of them. It’s a non-experimental type of quantitative research .

A correlation reflects the strength and/or direction of the association between two or more variables.

• A positive correlation means that both variables change in the same direction.
• A negative correlation means that the variables change in opposite directions.
• A zero correlation means there’s no relationship between the variables.

Longitudinal studies can last anywhere from weeks to decades, although they tend to be at least a year long.

The 1970 British Cohort Study , which has collected data on the lives of 17,000 Brits since their births in 1970, is one well-known example of a longitudinal study .

Longitudinal studies are better to establish the correct sequence of events, identify changes over time, and provide insight into cause-and-effect relationships, but they also tend to be more expensive and time-consuming than other types of studies.

Longitudinal studies and cross-sectional studies are two different types of research design . In a cross-sectional study you collect data from a population at a specific point in time; in a longitudinal study you repeatedly collect data from the same sample over an extended period of time.

Cross-sectional studies cannot establish a cause-and-effect relationship or analyse behaviour over a period of time. To investigate cause and effect, you need to do a longitudinal study or an experimental study .

Cross-sectional studies are less expensive and time-consuming than many other types of study. They can provide useful insights into a population’s characteristics and identify correlations for further research.

Sometimes only cross-sectional data are available for analysis; other times your research question may only require a cross-sectional study to answer it.

A hypothesis states your predictions about what your research will find. It is a tentative answer to your research question that has not yet been tested. For some research projects, you might have to write several hypotheses that address different aspects of your research question.

A hypothesis is not just a guess. It should be based on existing theories and knowledge. It also has to be testable, which means you can support or refute it through scientific research methods (such as experiments, observations, and statistical analysis of data).

A research hypothesis is your proposed answer to your research question. The research hypothesis usually includes an explanation (‘ x affects y because …’).

A statistical hypothesis, on the other hand, is a mathematical statement about a population parameter. Statistical hypotheses always come in pairs: the null and alternative hypotheses. In a well-designed study , the statistical hypotheses correspond logically to the research hypothesis.

Individual Likert-type questions are generally considered ordinal data , because the items have clear rank order, but don’t have an even distribution.

Overall Likert scale scores are sometimes treated as interval data. These scores are considered to have directionality and even spacing between them.

The type of data determines what statistical tests you should use to analyse your data.

A Likert scale is a rating scale that quantitatively assesses opinions, attitudes, or behaviours. It is made up of four or more questions that measure a single attitude or trait when response scores are combined.

To use a Likert scale in a survey , you present participants with Likert-type questions or statements, and a continuum of items, usually with five or seven possible responses, to capture their degree of agreement.

A questionnaire is a data collection tool or instrument, while a survey is an overarching research method that involves collecting and analysing data from people using questionnaires.

A true experiment (aka a controlled experiment) always includes at least one control group that doesn’t receive the experimental treatment.

However, some experiments use a within-subjects design to test treatments without a control group. In these designs, you usually compare one group’s outcomes before and after a treatment (instead of comparing outcomes between different groups).

For strong internal validity , it’s usually best to include a control group if possible. Without a control group, it’s harder to be certain that the outcome was caused by the experimental treatment and not by other variables.

An experimental group, also known as a treatment group, receives the treatment whose effect researchers wish to study, whereas a control group does not. They should be identical in all other ways.

In a controlled experiment , all extraneous variables are held constant so that they can’t influence the results. Controlled experiments require:

• A control group that receives a standard treatment, a fake treatment, or no treatment
• Random assignment of participants to ensure the groups are equivalent

Depending on your study topic, there are various other methods of controlling variables .

Questionnaires can be self-administered or researcher-administered.

Self-administered questionnaires can be delivered online or in paper-and-pen formats, in person or by post. All questions are standardised so that all respondents receive the same questions with identical wording.

Researcher-administered questionnaires are interviews that take place by phone, in person, or online between researchers and respondents. You can gain deeper insights by clarifying questions for respondents or asking follow-up questions.

You can organise the questions logically, with a clear progression from simple to complex, or randomly between respondents. A logical flow helps respondents process the questionnaire easier and quicker, but it may lead to bias. Randomisation can minimise the bias from order effects.

Closed-ended, or restricted-choice, questions offer respondents a fixed set of choices to select from. These questions are easier to answer quickly.

Open-ended or long-form questions allow respondents to answer in their own words. Because there are no restrictions on their choices, respondents can answer in ways that researchers may not have otherwise considered.

Naturalistic observation is a qualitative research method where you record the behaviours of your research subjects in real-world settings. You avoid interfering or influencing anything in a naturalistic observation.

You can think of naturalistic observation as ‘people watching’ with a purpose.

Naturalistic observation is a valuable tool because of its flexibility, external validity , and suitability for topics that can’t be studied in a lab setting.

The downsides of naturalistic observation include its lack of scientific control , ethical considerations , and potential for bias from observers and subjects.

You can use several tactics to minimise observer bias .

• Use masking (blinding) to hide the purpose of your study from all observers.
• Triangulate your data with different data collection methods or sources.
• Use multiple observers and ensure inter-rater reliability.
• Train your observers to make sure data is consistently recorded between them.
• Standardise your observation procedures to make sure they are structured and clear.

The observer-expectancy effect occurs when researchers influence the results of their own study through interactions with participants.

Researchers’ own beliefs and expectations about the study results may unintentionally influence participants through demand characteristics .

Observer bias occurs when a researcher’s expectations, opinions, or prejudices influence what they perceive or record in a study. It usually affects studies when observers are aware of the research aims or hypotheses. This type of research bias is also called detection bias or ascertainment bias .

Data cleaning is necessary for valid and appropriate analyses. Dirty data contain inconsistencies or errors , but cleaning your data helps you minimise or resolve these.

Without data cleaning, you could end up with a Type I or II error in your conclusion. These types of erroneous conclusions can be practically significant with important consequences, because they lead to misplaced investments or missed opportunities.

Data cleaning involves spotting and resolving potential data inconsistencies or errors to improve your data quality. An error is any value (e.g., recorded weight) that doesn’t reflect the true value (e.g., actual weight) of something that’s being measured.

In this process, you review, analyse, detect, modify, or remove ‘dirty’ data to make your dataset ‘clean’. Data cleaning is also called data cleansing or data scrubbing.

Data cleaning takes place between data collection and data analyses. But you can use some methods even before collecting data.

For clean data, you should start by designing measures that collect valid data. Data validation at the time of data entry or collection helps you minimize the amount of data cleaning you’ll need to do.

After data collection, you can use data standardisation and data transformation to clean your data. You’ll also deal with any missing values, outliers, and duplicate values.

Clean data are valid, accurate, complete, consistent, unique, and uniform. Dirty data include inconsistencies and errors.

Dirty data can come from any part of the research process, including poor research design , inappropriate measurement materials, or flawed data entry.

Random assignment is used in experiments with a between-groups or independent measures design. In this research design, there’s usually a control group and one or more experimental groups. Random assignment helps ensure that the groups are comparable.

In general, you should always use random assignment in this type of experimental design when it is ethically possible and makes sense for your study topic.

Random selection, or random sampling , is a way of selecting members of a population for your study’s sample.

In contrast, random assignment is a way of sorting the sample into control and experimental groups.

Random sampling enhances the external validity or generalisability of your results, while random assignment improves the internal validity of your study.

To implement random assignment , assign a unique number to every member of your study’s sample .

Then, you can use a random number generator or a lottery method to randomly assign each number to a control or experimental group. You can also do so manually, by flipping a coin or rolling a die to randomly assign participants to groups.

Exploratory research is often used when the issue you’re studying is new or when the data collection process is challenging for some reason.

You can use exploratory research if you have a general idea or a specific question that you want to study but there is no preexisting knowledge or paradigm with which to study it.

Exploratory research is a methodology approach that explores research questions that have not previously been studied in depth. It is often used when the issue you’re studying is new, or the data collection process is challenging in some way.

Explanatory research is used to investigate how or why a phenomenon occurs. Therefore, this type of research is often one of the first stages in the research process , serving as a jumping-off point for future research.

Explanatory research is a research method used to investigate how or why something occurs when only a small amount of information is available pertaining to that topic. It can help you increase your understanding of a given topic.

Blinding means hiding who is assigned to the treatment group and who is assigned to the control group in an experiment .

Blinding is important to reduce bias (e.g., observer bias , demand characteristics ) and ensure a study’s internal validity .

If participants know whether they are in a control or treatment group , they may adjust their behaviour in ways that affect the outcome that researchers are trying to measure. If the people administering the treatment are aware of group assignment, they may treat participants differently and thus directly or indirectly influence the final results.

• In a single-blind study , only the participants are blinded.
• In a double-blind study , both participants and experimenters are blinded.
• In a triple-blind study , the assignment is hidden not only from participants and experimenters, but also from the researchers analysing the data.

Many academic fields use peer review , largely to determine whether a manuscript is suitable for publication. Peer review enhances the credibility of the published manuscript.

However, peer review is also common in non-academic settings. The United Nations, the European Union, and many individual nations use peer review to evaluate grant applications. It is also widely used in medical and health-related fields as a teaching or quality-of-care measure.

Peer assessment is often used in the classroom as a pedagogical tool. Both receiving feedback and providing it are thought to enhance the learning process, helping students think critically and collaboratively.

Peer review can stop obviously problematic, falsified, or otherwise untrustworthy research from being published. It also represents an excellent opportunity to get feedback from renowned experts in your field.

It acts as a first defence, helping you ensure your argument is clear and that there are no gaps, vague terms, or unanswered questions for readers who weren’t involved in the research process.

Peer-reviewed articles are considered a highly credible source due to this stringent process they go through before publication.

In general, the peer review process follows the following steps:

• First, the author submits the manuscript to the editor.
• Reject the manuscript and send it back to author, or
• Send it onward to the selected peer reviewer(s)
• Next, the peer review process occurs. The reviewer provides feedback, addressing any major or minor issues with the manuscript, and gives their advice regarding what edits should be made.
• Lastly, the edited manuscript is sent back to the author. They input the edits, and resubmit it to the editor for publication.

Peer review is a process of evaluating submissions to an academic journal. Utilising rigorous criteria, a panel of reviewers in the same subject area decide whether to accept each submission for publication.

For this reason, academic journals are often considered among the most credible sources you can use in a research project – provided that the journal itself is trustworthy and well regarded.

Anonymity means you don’t know who the participants are, while confidentiality means you know who they are but remove identifying information from your research report. Both are important ethical considerations .

You can only guarantee anonymity by not collecting any personally identifying information – for example, names, phone numbers, email addresses, IP addresses, physical characteristics, photos, or videos.

You can keep data confidential by using aggregate information in your research report, so that you only refer to groups of participants rather than individuals.

Research misconduct means making up or falsifying data, manipulating data analyses, or misrepresenting results in research reports. It’s a form of academic fraud.

These actions are committed intentionally and can have serious consequences; research misconduct is not a simple mistake or a point of disagreement but a serious ethical failure.

Research ethics matter for scientific integrity, human rights and dignity, and collaboration between science and society. These principles make sure that participation in studies is voluntary, informed, and safe.

Ethical considerations in research are a set of principles that guide your research designs and practices. These principles include voluntary participation, informed consent, anonymity, confidentiality, potential for harm, and results communication.

Scientists and researchers must always adhere to a certain code of conduct when collecting data from others .

These considerations protect the rights of research participants, enhance research validity , and maintain scientific integrity.

A systematic review is secondary research because it uses existing research. You don’t collect new data yourself.

The two main types of social desirability bias are:

• Self-deceptive enhancement (self-deception): The tendency to see oneself in a favorable light without realizing it.
• Impression managemen t (other-deception): The tendency to inflate one’s abilities or achievement in order to make a good impression on other people.

Demand characteristics are aspects of experiments that may give away the research objective to participants. Social desirability bias occurs when participants automatically try to respond in ways that make them seem likeable in a study, even if it means misrepresenting how they truly feel.

Participants may use demand characteristics to infer social norms or experimenter expectancies and act in socially desirable ways, so you should try to control for demand characteristics wherever possible.

Response bias refers to conditions or factors that take place during the process of responding to surveys, affecting the responses. One type of response bias is social desirability bias .

When your population is large in size, geographically dispersed, or difficult to contact, it’s necessary to use a sampling method .

This allows you to gather information from a smaller part of the population, i.e. the sample, and make accurate statements by using statistical analysis. A few sampling methods include simple random sampling , convenience sampling , and snowball sampling .

Stratified and cluster sampling may look similar, but bear in mind that groups created in cluster sampling are heterogeneous , so the individual characteristics in the cluster vary. In contrast, groups created in stratified sampling are homogeneous , as units share characteristics.

Relatedly, in cluster sampling you randomly select entire groups and include all units of each group in your sample. However, in stratified sampling, you select some units of all groups and include them in your sample. In this way, both methods can ensure that your sample is representative of the target population .

A sampling frame is a list of every member in the entire population . It is important that the sampling frame is as complete as possible, so that your sample accurately reflects your population.

Convenience sampling and quota sampling are both non-probability sampling methods. They both use non-random criteria like availability, geographical proximity, or expert knowledge to recruit study participants.

However, in convenience sampling, you continue to sample units or cases until you reach the required sample size.

In quota sampling, you first need to divide your population of interest into subgroups (strata) and estimate their proportions (quota) in the population. Then you can start your data collection , using convenience sampling to recruit participants, until the proportions in each subgroup coincide with the estimated proportions in the population.

Random sampling or probability sampling is based on random selection. This means that each unit has an equal chance (i.e., equal probability) of being included in the sample.

On the other hand, convenience sampling involves stopping people at random, which means that not everyone has an equal chance of being selected depending on the place, time, or day you are collecting your data.

Stratified sampling and quota sampling both involve dividing the population into subgroups and selecting units from each subgroup. The purpose in both cases is to select a representative sample and/or to allow comparisons between subgroups.

The main difference is that in stratified sampling, you draw a random sample from each subgroup ( probability sampling ). In quota sampling you select a predetermined number or proportion of units, in a non-random manner ( non-probability sampling ).

Snowball sampling is best used in the following cases:

• If there is no sampling frame available (e.g., people with a rare disease)
• If the population of interest is hard to access or locate (e.g., people experiencing homelessness)
• If the research focuses on a sensitive topic (e.g., extra-marital affairs)

Snowball sampling relies on the use of referrals. Here, the researcher recruits one or more initial participants, who then recruit the next ones. 

Participants share similar characteristics and/or know each other. Because of this, not every member of the population has an equal chance of being included in the sample, giving rise to sampling bias .

Snowball sampling is a non-probability sampling method , where there is not an equal chance for every member of the population to be included in the sample .

This means that you cannot use inferential statistics and make generalisations – often the goal of quantitative research . As such, a snowball sample is not representative of the target population, and is usually a better fit for qualitative research .

Snowball sampling is a non-probability sampling method . Unlike probability sampling (which involves some form of random selection ), the initial individuals selected to be studied are the ones who recruit new participants.

Because not every member of the target population has an equal chance of being recruited into the sample, selection in snowball sampling is non-random.

Reproducibility and replicability are related terms.

• Reproducing research entails reanalysing the existing data in the same manner.
• Replicating (or repeating ) the research entails reconducting the entire analysis, including the collection of new data . 
• A successful reproduction shows that the data analyses were conducted in a fair and honest manner.
• A successful replication shows that the reliability of the results is high.

The reproducibility and replicability of a study can be ensured by writing a transparent, detailed method section and using clear, unambiguous language.

Convergent validity and discriminant validity are both subtypes of construct validity . Together, they help you evaluate whether a test measures the concept it was designed to measure.

• Convergent validity indicates whether a test that is designed to measure a particular construct correlates with other tests that assess the same or similar construct.
• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related

You need to assess both in order to demonstrate construct validity. Neither one alone is sufficient for establishing construct validity.

Construct validity has convergent and discriminant subtypes. They assist determine if a test measures the intended notion.

Content validity shows you how accurately a test or other measurement method taps  into the various aspects of the specific construct you are researching.

In other words, it helps you answer the question: “does the test measure all aspects of the construct I want to measure?” If it does, then the test has high content validity.

The higher the content validity, the more accurate the measurement of the construct.

If the test fails to include parts of the construct, or irrelevant parts are included, the validity of the instrument is threatened, which brings your results into question.

Construct validity refers to how well a test measures the concept (or construct) it was designed to measure. Assessing construct validity is especially important when you’re researching concepts that can’t be quantified and/or are intangible, like introversion. To ensure construct validity your test should be based on known indicators of introversion ( operationalisation ).

On the other hand, content validity assesses how well the test represents all aspects of the construct. If some aspects are missing or irrelevant parts are included, the test has low content validity.

Face validity and content validity are similar in that they both evaluate how suitable the content of a test is. The difference is that face validity is subjective, and assesses content at surface level.

When a test has strong face validity, anyone would agree that the test’s questions appear to measure what they are intended to measure.

For example, looking at a 4th grade math test consisting of problems in which students have to add and multiply, most people would agree that it has strong face validity (i.e., it looks like a math test).

On the other hand, content validity evaluates how well a test represents all the aspects of a topic. Assessing content validity is more systematic and relies on expert evaluation. of each question, analysing whether each one covers the aspects that the test was designed to cover.

A 4th grade math test would have high content validity if it covered all the skills taught in that grade. Experts(in this case, math teachers), would have to evaluate the content validity by comparing the test to the learning objectives.

• Discriminant validity indicates whether two tests that should not be highly related to each other are indeed not related. This type of validity is also called divergent validity .

Criterion validity and construct validity are both types of measurement validity . In other words, they both show you how accurately a method measures something.

While construct validity is the degree to which a test or other measurement method measures what it claims to measure, criterion validity is the degree to which a test can predictively (in the future) or concurrently (in the present) measure something.

Construct validity is often considered the overarching type of measurement validity . You need to have face validity , content validity , and criterion validity in order to achieve construct validity.

Attrition refers to participants leaving a study. It always happens to some extent – for example, in randomised control trials for medical research.

Differential attrition occurs when attrition or dropout rates differ systematically between the intervention and the control group . As a result, the characteristics of the participants who drop out differ from the characteristics of those who stay in the study. Because of this, study results may be biased .

Criterion validity evaluates how well a test measures the outcome it was designed to measure. An outcome can be, for example, the onset of a disease.

Criterion validity consists of two subtypes depending on the time at which the two measures (the criterion and your test) are obtained:

• Concurrent validity is a validation strategy where the the scores of a test and the criterion are obtained at the same time
• Predictive validity is a validation strategy where the criterion variables are measured after the scores of the test

Validity tells you how accurately a method measures what it was designed to measure. There are 4 main types of validity :

• Construct validity : Does the test measure the construct it was designed to measure?
• Face validity : Does the test appear to be suitable for its objectives ?
• Content validity : Does the test cover all relevant parts of the construct it aims to measure.
• Criterion validity : Do the results accurately measure the concrete outcome they are designed to measure?

Convergent validity shows how much a measure of one construct aligns with other measures of the same or related constructs .

On the other hand, concurrent validity is about how a measure matches up to some known criterion or gold standard, which can be another measure.

Although both types of validity are established by calculating the association or correlation between a test score and another variable , they represent distinct validation methods.

The purpose of theory-testing mode is to find evidence in order to disprove, refine, or support a theory. As such, generalisability is not the aim of theory-testing mode.

Due to this, the priority of researchers in theory-testing mode is to eliminate alternative causes for relationships between variables . In other words, they prioritise internal validity over external validity , including ecological validity .

Inclusion and exclusion criteria are typically presented and discussed in the methodology section of your thesis or dissertation .

Inclusion and exclusion criteria are predominantly used in non-probability sampling . In purposive sampling and snowball sampling , restrictions apply as to who can be included in the sample .

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

• Budget constraints or any specifics of grant funding
• Your proposed timeline and duration
• Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
• Any inclusion and exclusion criteria
• Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

To make quantitative observations , you need to use instruments that are capable of measuring the quantity you want to observe. For example, you might use a ruler to measure the length of an object or a thermometer to measure its temperature.

Quantitative observations involve measuring or counting something and expressing the result in numerical form, while qualitative observations involve describing something in non-numerical terms, such as its appearance, texture, or color.

The Scribbr Reference Generator is developed using the open-source Citation Style Language (CSL) project and Frank Bennett’s citeproc-js . It’s the same technology used by dozens of other popular citation tools, including Mendeley and Zotero.

You can find all the citation styles and locales used in the Scribbr Reference Generator in our publicly accessible repository on Github .

To paraphrase effectively, don’t just take the original sentence and swap out some of the words for synonyms. Instead, try:

• Reformulating the sentence (e.g., change active to passive , or start from a different point)
• Combining information from multiple sentences into one
• Leaving out information from the original that isn’t relevant to your point
• Using synonyms where they don’t distort the meaning

The main point is to ensure you don’t just copy the structure of the original text, but instead reformulate the idea in your own words.

Plagiarism means using someone else’s words or ideas and passing them off as your own. Paraphrasing means putting someone else’s ideas into your own words.

So when does paraphrasing count as plagiarism?

• Paraphrasing is plagiarism if you don’t properly credit the original author.
• Paraphrasing is plagiarism if your text is too close to the original wording (even if you cite the source). If you directly copy a sentence or phrase, you should quote it instead.
• Paraphrasing  is not plagiarism if you put the author’s ideas completely into your own words and properly reference the source .

To present information from other sources in academic writing , it’s best to paraphrase in most cases. This shows that you’ve understood the ideas you’re discussing and incorporates them into your text smoothly.

It’s appropriate to quote when:

• Changing the phrasing would distort the meaning of the original text
• You want to discuss the author’s language choices (e.g., in literary analysis )
• You’re presenting a precise definition
• You’re looking in depth at a specific claim

A quote is an exact copy of someone else’s words, usually enclosed in quotation marks and credited to the original author or speaker.

Every time you quote a source , you must include a correctly formatted in-text citation . This looks slightly different depending on the citation style .

For example, a direct quote in APA is cited like this: ‘This is a quote’ (Streefkerk, 2020, p. 5).

Every in-text citation should also correspond to a full reference at the end of your paper.

In scientific subjects, the information itself is more important than how it was expressed, so quoting should generally be kept to a minimum. In the arts and humanities, however, well-chosen quotes are often essential to a good paper.

In social sciences, it varies. If your research is mainly quantitative , you won’t include many quotes, but if it’s more qualitative , you may need to quote from the data you collected .

As a general guideline, quotes should take up no more than 5–10% of your paper. If in doubt, check with your instructor or supervisor how much quoting is appropriate in your field.

If you’re quoting from a text that paraphrases or summarises other sources and cites them in parentheses , APA  recommends retaining the citations as part of the quote:

• Smith states that ‘the literature on this topic (Jones, 2015; Sill, 2019; Paulson, 2020) shows no clear consensus’ (Smith, 2019, p. 4).

Footnote or endnote numbers that appear within quoted text should be omitted.

If you want to cite an indirect source (one you’ve only seen quoted in another source), either locate the original source or use the phrase ‘as cited in’ in your citation.

A block quote is a long quote formatted as a separate ‘block’ of text. Instead of using quotation marks , you place the quote on a new line, and indent the entire quote to mark it apart from your own words.

APA uses block quotes for quotes that are 40 words or longer.

A credible source should pass the CRAAP test  and follow these guidelines:

• The information should be up to date and current.
• The author and publication should be a trusted authority on the subject you are researching.
• The sources the author cited should be easy to find, clear, and unbiased.
• For a web source, the URL and layout should signify that it is trustworthy.

Common examples of primary sources include interview transcripts , photographs, novels, paintings, films, historical documents, and official statistics.

Anything you directly analyze or use as first-hand evidence can be a primary source, including qualitative or quantitative data that you collected yourself.

Common examples of secondary sources include academic books, journal articles , reviews, essays , and textbooks.

Anything that summarizes, evaluates or interprets primary sources can be a secondary source. If a source gives you an overview of background information or presents another researcher’s ideas on your topic, it is probably a secondary source.

To determine if a source is primary or secondary, ask yourself:

• Was the source created by someone directly involved in the events you’re studying (primary), or by another researcher (secondary)?
• Does the source provide original information (primary), or does it summarize information from other sources (secondary)?
• Are you directly analyzing the source itself (primary), or only using it for background information (secondary)?

Some types of sources are nearly always primary: works of art and literature, raw statistical data, official documents and records, and personal communications (e.g. letters, interviews ). If you use one of these in your research, it is probably a primary source.

Primary sources are often considered the most credible in terms of providing evidence for your argument, as they give you direct evidence of what you are researching. However, it’s up to you to ensure the information they provide is reliable and accurate.

Always make sure to properly cite your sources to avoid plagiarism .

A fictional movie is usually a primary source. A documentary can be either primary or secondary depending on the context.

If you are directly analysing some aspect of the movie itself – for example, the cinematography, narrative techniques, or social context – the movie is a primary source.

If you use the movie for background information or analysis about your topic – for example, to learn about a historical event or a scientific discovery – the movie is a secondary source.

Whether it’s primary or secondary, always properly cite the movie in the citation style you are using. Learn how to create an MLA movie citation or an APA movie citation .

Articles in newspapers and magazines can be primary or secondary depending on the focus of your research.

In historical studies, old articles are used as primary sources that give direct evidence about the time period. In social and communication studies, articles are used as primary sources to analyse language and social relations (for example, by conducting content analysis or discourse analysis ).

If you are not analysing the article itself, but only using it for background information or facts about your topic, then the article is a secondary source.

In academic writing , there are three main situations where quoting is the best choice:

• To analyse the author’s language (e.g., in a literary analysis essay )
• To give evidence from primary sources
• To accurately present a precise definition or argument

Don’t overuse quotes; your own voice should be dominant. If you just want to provide information from a source, it’s usually better to paraphrase or summarise .

Your list of tables and figures should go directly after your table of contents in your thesis or dissertation.

Lists of figures and tables are often not required, and they aren’t particularly common. They specifically aren’t required for APA Style, though you should be careful to follow their other guidelines for figures and tables .

If you have many figures and tables in your thesis or dissertation, include one may help you stay organised. Your educational institution may require them, so be sure to check their guidelines.

Copyright information can usually be found wherever the table or figure was published. For example, for a diagram in a journal article , look on the journal’s website or the database where you found the article. Images found on sites like Flickr are listed with clear copyright information.

If you find that permission is required to reproduce the material, be sure to contact the author or publisher and ask for it.

A list of figures and tables compiles all of the figures and tables that you used in your thesis or dissertation and displays them with the page number where they can be found.

APA doesn’t require you to include a list of tables or a list of figures . However, it is advisable to do so if your text is long enough to feature a table of contents and it includes a lot of tables and/or figures .

A list of tables and list of figures appear (in that order) after your table of contents, and are presented in a similar way.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. Your glossary only needs to include terms that your reader may not be familiar with, and is intended to enhance their understanding of your work.

Definitional terms often fall into the category of common knowledge , meaning that they don’t necessarily have to be cited. This guidance can apply to your thesis or dissertation glossary as well.

However, if you’d prefer to cite your sources , you can follow guidance for citing dictionary entries in MLA or APA style for your glossary.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, an index is a list of the contents of your work organised by page number.

Glossaries are not mandatory, but if you use a lot of technical or field-specific terms, it may improve readability to add one to your thesis or dissertation. Your educational institution may also require them, so be sure to check their specific guidelines.

A glossary is a collection of words pertaining to a specific topic. In your thesis or dissertation, it’s a list of all terms you used that may not immediately be obvious to your reader. In contrast, dictionaries are more general collections of words.

The title page of your thesis or dissertation should include your name, department, institution, degree program, and submission date.

The title page of your thesis or dissertation goes first, before all other content or lists that you may choose to include.

Usually, no title page is needed in an MLA paper . A header is generally included at the top of the first page instead. The exceptions are when:

• Your instructor requires one, or
• Your paper is a group project

In those cases, you should use a title page instead of a header, listing the same information but on a separate page.

When you mention different chapters within your text, it’s considered best to use Roman numerals for most citation styles. However, the most important thing here is to remain consistent whenever using numbers in your dissertation .

A thesis or dissertation outline is one of the most critical first steps in your writing process. It helps you to lay out and organise your ideas and can provide you with a roadmap for deciding what kind of research you’d like to undertake.

Generally, an outline contains information on the different sections included in your thesis or dissertation, such as:

• Your anticipated title
• Your abstract
• Your chapters (sometimes subdivided into further topics like literature review, research methods, avenues for future research, etc.)

While a theoretical framework describes the theoretical underpinnings of your work based on existing research, a conceptual framework allows you to draw your own conclusions, mapping out the variables you may use in your study and the interplay between them.

A literature review and a theoretical framework are not the same thing and cannot be used interchangeably. While a theoretical framework describes the theoretical underpinnings of your work, a literature review critically evaluates existing research relating to your topic. You’ll likely need both in your dissertation .

A theoretical framework can sometimes be integrated into a  literature review chapter , but it can also be included as its own chapter or section in your dissertation . As a rule of thumb, if your research involves dealing with a lot of complex theories, it’s a good idea to include a separate theoretical framework chapter.

An abstract is a concise summary of an academic text (such as a journal article or dissertation ). It serves two main purposes:

• To help potential readers determine the relevance of your paper for their own research.
• To communicate your key findings to those who don’t have time to read the whole paper.

Abstracts are often indexed along with keywords on academic databases, so they make your work more easily findable. Since the abstract is the first thing any reader sees, it’s important that it clearly and accurately summarises the contents of your paper.

The abstract is the very last thing you write. You should only write it after your research is complete, so that you can accurately summarize the entirety of your thesis or paper.

Avoid citing sources in your abstract . There are two reasons for this:

• The abstract should focus on your original research, not on the work of others.
• The abstract should be self-contained and fully understandable without reference to other sources.

There are some circumstances where you might need to mention other sources in an abstract: for example, if your research responds directly to another study or focuses on the work of a single theorist. In general, though, don’t include citations unless absolutely necessary.

The abstract appears on its own page, after the title page and acknowledgements but before the table of contents .

Results are usually written in the past tense , because they are describing the outcome of completed actions.

The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.

In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.

Formulating a main research question can be a difficult task. Overall, your question should contribute to solving the problem that you have defined in your problem statement .

However, it should also fulfill criteria in three main areas:

• Researchability
• Feasibility and specificity
• Relevance and originality

The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.

A noun is a word that represents a person, thing, concept, or place (e.g., ‘John’, ‘house’, ‘affinity’, ‘river’). Most sentences contain at least one noun or pronoun .

Nouns are often, but not always, preceded by an article (‘the’, ‘a’, or ‘an’) and/or another determiner such as an adjective.

There are many ways to categorize nouns into various types, and the same noun can fall into multiple categories or even change types depending on context.

Some of the main types of nouns are:

• Common nouns and proper nouns
• Countable and uncountable nouns
• Concrete and abstract nouns
• Collective nouns
• Possessive nouns
• Attributive nouns
• Appositive nouns
• Generic nouns

Pronouns are words like ‘I’, ‘she’, and ‘they’ that are used in a similar way to nouns . They stand in for a noun that has already been mentioned or refer to yourself and other people.

Pronouns can function just like nouns as the head of a noun phrase and as the subject or object of a verb. However, pronouns change their forms (e.g., from ‘I’ to ‘me’) depending on the grammatical context they’re used in, whereas nouns usually don’t.

Common nouns are words for types of things, people, and places, such as ‘dog’, ‘professor’, and ‘city’. They are not capitalised and are typically used in combination with articles and other determiners.

Proper nouns are words for specific things, people, and places, such as ‘Max’, ‘Dr Prakash’, and ‘London’. They are always capitalised and usually aren’t combined with articles and other determiners.

A proper adjective is an adjective that was derived from a proper noun and is therefore capitalised .

Proper adjectives include words for nationalities, languages, and ethnicities (e.g., ‘Japanese’, ‘Inuit’, ‘French’) and words derived from people’s names (e.g., ‘Bayesian’, ‘Orwellian’).

The names of seasons (e.g., ‘spring’) are treated as common nouns in English and therefore not capitalised . People often assume they are proper nouns, but this is an error.

The names of days and months, however, are capitalised since they’re treated as proper nouns in English (e.g., ‘Wednesday’, ‘January’).

No, as a general rule, academic concepts, disciplines, theories, models, etc. are treated as common nouns , not proper nouns , and therefore not capitalised . For example, ‘five-factor model of personality’ or ‘analytic philosophy’.

However, proper nouns that appear within the name of an academic concept (such as the name of the inventor) are capitalised as usual. For example, ‘Darwin’s theory of evolution’ or ‘ Student’s t table ‘.

Collective nouns are most commonly treated as singular (e.g., ‘the herd is grazing’), but usage differs between US and UK English :

• In US English, it’s standard to treat all collective nouns as singular, even when they are plural in appearance (e.g., ‘The Rolling Stones is …’). Using the plural form is usually seen as incorrect.
• In UK English, collective nouns can be treated as singular or plural depending on context. It’s quite common to use the plural form, especially when the noun looks plural (e.g., ‘The Rolling Stones are …’).

The plural of “crisis” is “crises”. It’s a loanword from Latin and retains its original Latin plural noun form (similar to “analyses” and “bases”). It’s wrong to write “crisises”.

For example, you might write “Several crises destabilized the regime.”

Normally, the plural of “fish” is the same as the singular: “fish”. It’s one of a group of irregular plural nouns in English that are identical to the corresponding singular nouns (e.g., “moose”, “sheep”). For example, you might write “The fish scatter as the shark approaches.”

If you’re referring to several species of fish, though, the regular plural “fishes” is often used instead. For example, “The aquarium contains many different fishes , including trout and carp.”

The correct plural of “octopus” is “octopuses”.

People often write “octopi” instead because they assume that the plural noun is formed in the same way as Latin loanwords such as “fungus/fungi”. But “octopus” actually comes from Greek, where its original plural is “octopodes”. In English, it instead has the regular plural form “octopuses”.

For example, you might write “There are four octopuses in the aquarium.”

The plural of “moose” is the same as the singular: “moose”. It’s one of a group of plural nouns in English that are identical to the corresponding singular nouns. So it’s wrong to write “mooses”.

For example, you might write “There are several moose in the forest.”

Bias in research affects the validity and reliability of your findings, leading to false conclusions and a misinterpretation of the truth. This can have serious implications in areas like medical research where, for example, a new form of treatment may be evaluated.

Observer bias occurs when the researcher’s assumptions, views, or preconceptions influence what they see and record in a study, while actor–observer bias refers to situations where respondents attribute internal factors (e.g., bad character) to justify other’s behaviour and external factors (difficult circumstances) to justify the same behaviour in themselves.

Response bias is a general term used to describe a number of different conditions or factors that cue respondents to provide inaccurate or false answers during surveys or interviews . These factors range from the interviewer’s perceived social position or appearance to the the phrasing of questions in surveys.

Nonresponse bias occurs when the people who complete a survey are different from those who did not, in ways that are relevant to the research topic. Nonresponse can happen either because people are not willing or not able to participate.

In research, demand characteristics are cues that might indicate the aim of a study to participants. These cues can lead to participants changing their behaviors or responses based on what they think the research is about.

Demand characteristics are common problems in psychology experiments and other social science studies because they can bias your research findings.

Demand characteristics are a type of extraneous variable that can affect the outcomes of the study. They can invalidate studies by providing an alternative explanation for the results.

These cues may nudge participants to consciously or unconsciously change their responses, and they pose a threat to both internal and external validity . You can’t be sure that your independent variable manipulation worked, or that your findings can be applied to other people or settings.

You can control demand characteristics by taking a few precautions in your research design and materials.

Use these measures:

• Deception: Hide the purpose of the study from participants
• Between-groups design : Give each participant only one independent variable treatment
• Double-blind design : Conceal the assignment of groups from participants and yourself
• Implicit measures: Use indirect or hidden measurements for your variables

Some attrition is normal and to be expected in research. However, the type of attrition is important because systematic research bias can distort your findings. Attrition bias can lead to inaccurate results because it affects internal and/or external validity .

To avoid attrition bias , applying some of these measures can help you reduce participant dropout (attrition) by making it easy and appealing for participants to stay.

• Provide compensation (e.g., cash or gift cards) for attending every session
• Minimise the number of follow-ups as much as possible
• Make all follow-ups brief, flexible, and convenient for participants
• Send participants routine reminders to schedule follow-ups
• Recruit more participants than you need for your sample (oversample)
• Maintain detailed contact information so you can get in touch with participants even if they move

If you have a small amount of attrition bias , you can use a few statistical methods to try to make up for this research bias .

Multiple imputation involves using simulations to replace the missing data with likely values. Alternatively, you can use sample weighting to make up for the uneven balance of participants in your sample.

Placebos are used in medical research for new medication or therapies, called clinical trials. In these trials some people are given a placebo, while others are given the new medication being tested.

The purpose is to determine how effective the new medication is: if it benefits people beyond a predefined threshold as compared to the placebo, it’s considered effective.

Although there is no definite answer to what causes the placebo effect , researchers propose a number of explanations such as the power of suggestion, doctor-patient interaction, classical conditioning, etc.

Belief bias and confirmation bias are both types of cognitive bias that impact our judgment and decision-making.

Confirmation bias relates to how we perceive and judge evidence. We tend to seek out and prefer information that supports our preexisting beliefs, ignoring any information that contradicts those beliefs.

Belief bias describes the tendency to judge an argument based on how plausible the conclusion seems to us, rather than how much evidence is provided to support it during the course of the argument.

Positivity bias is phenomenon that occurs when a person judges individual members of a group positively, even when they have negative impressions or judgments of the group as a whole. Positivity bias is closely related to optimism bias , or the e xpectation that things will work out well, even if rationality suggests that problems are inevitable in life.

Perception bias is a problem because it prevents us from seeing situations or people objectively. Rather, our expectations, beliefs, or emotions interfere with how we interpret reality. This, in turn, can cause us to misjudge ourselves or others. For example, our prejudices can interfere with whether we perceive people’s faces as friendly or unfriendly.

There are many ways to categorize adjectives into various types. An adjective can fall into one or more of these categories depending on how it is used.

Some of the main types of adjectives are:

• Attributive adjectives
• Predicative adjectives
• Comparative adjectives
• Superlative adjectives
• Coordinate adjectives
• Appositive adjectives
• Compound adjectives
• Participial adjectives
• Proper adjectives
• Denominal adjectives
• Nominal adjectives

Cardinal numbers (e.g., one, two, three) can be placed before a noun to indicate quantity (e.g., one apple). While these are sometimes referred to as ‘numeral adjectives ‘, they are more accurately categorised as determiners or quantifiers.

Proper adjectives are adjectives formed from a proper noun (i.e., the name of a specific person, place, or thing) that are used to indicate origin. Like proper nouns, proper adjectives are always capitalised (e.g., Newtonian, Marxian, African).

The cost of proofreading depends on the type and length of text, the turnaround time, and the level of services required. Most proofreading companies charge per word or page, while freelancers sometimes charge an hourly rate.

For proofreading alone, which involves only basic corrections of typos and formatting mistakes, you might pay as little as £0.01 per word, but in many cases, your text will also require some level of editing , which costs slightly more.

It’s often possible to purchase combined proofreading and editing services and calculate the price in advance based on your requirements.

Then and than are two commonly confused words . In the context of ‘better than’, you use ‘than’ with an ‘a’.

• Julie is better than Jesse.
• I’d rather spend my time with you than with him.
• I understand Eoghan’s point of view better than Claudia’s.

Use to and used to are commonly confused words . In the case of ‘used to do’, the latter (with ‘d’) is correct, since you’re describing an action or state in the past.

• I used to do laundry once a week.
• They used to do each other’s hair.
• We used to do the dishes every day .

There are numerous synonyms and near synonyms for the various meanings of “ favour ”:

There are numerous synonyms and near synonyms for the two meanings of “ favoured ”:

No one (two words) is an indefinite pronoun meaning ‘nobody’. People sometimes mistakenly write ‘noone’, but this is incorrect and should be avoided. ‘No-one’, with a hyphen, is also acceptable in UK English .

Nobody and no one are both indefinite pronouns meaning ‘no person’. They can be used interchangeably (e.g., ‘nobody is home’ means the same as ‘no one is home’).

Some synonyms and near synonyms of  every time include:

• Without exception

‘Everytime’ is sometimes used to mean ‘each time’ or ‘whenever’. However, this is incorrect and should be avoided. The correct phrase is every time   (two words).

Yes, the conjunction because is a compound word , but one with a long history. It originates in Middle English from the preposition “bi” (“by”) and the noun “cause”. Over time, the open compound “bi cause” became the closed compound “because”, which we use today.

Though it’s spelled this way now, the verb “be” is not one of the words that makes up “because”.

Yes, today is a compound word , but a very old one. It wasn’t originally formed from the preposition “to” and the noun “day”; rather, it originates from their Old English equivalents, “tō” and “dæġe”.

In the past, it was sometimes written as a hyphenated compound: “to-day”. But the hyphen is no longer included; it’s always “today” now (“to day” is also wrong).

IEEE citation format is defined by the Institute of Electrical and Electronics Engineers and used in their publications.

It’s also a widely used citation style for students in technical fields like electrical and electronic engineering, computer science, telecommunications, and computer engineering.

An IEEE in-text citation consists of a number in brackets at the relevant point in the text, which points the reader to the right entry in the numbered reference list at the end of the paper. For example, ‘Smith [1] states that …’

A location marker such as a page number is also included within the brackets when needed: ‘Smith [1, p. 13] argues …’

The IEEE reference page consists of a list of references numbered in the order they were cited in the text. The title ‘References’ appears in bold at the top, either left-aligned or centered.

The numbers appear in square brackets on the left-hand side of the page. The reference entries are indented consistently to separate them from the numbers. Entries are single-spaced, with a normal paragraph break between them.

If you cite the same source more than once in your writing, use the same number for all of the IEEE in-text citations for that source, and only include it on the IEEE reference page once. The source is numbered based on the first time you cite it.

For example, the fourth source you cite in your paper is numbered [4]. If you cite it again later, you still cite it as [4]. You can cite different parts of the source each time by adding page numbers [4, p. 15].

A verb is a word that indicates a physical action (e.g., ‘drive’), a mental action (e.g., ‘think’) or a state of being (e.g., ‘exist’). Every sentence contains a verb.

Verbs are almost always used along with a noun or pronoun to describe what the noun or pronoun is doing.

There are many ways to categorize verbs into various types. A verb can fall into one or more of these categories depending on how it is used.

Some of the main types of verbs are:

• Regular verbs
• Irregular verbs
• Transitive verbs
• Intransitive verbs
• Dynamic verbs
• Stative verbs
• Linking verbs
• Auxiliary verbs
• Modal verbs
• Phrasal verbs

Regular verbs are verbs whose simple past and past participle are formed by adding the suffix ‘-ed’ (e.g., ‘walked’).

Irregular verbs are verbs that form their simple past and past participles in some way other than by adding the suffix ‘-ed’ (e.g., ‘sat’).

The indefinite articles a and an are used to refer to a general or unspecified version of a noun (e.g., a house). Which indefinite article you use depends on the pronunciation of the word that follows it.

• A is used for words that begin with a consonant sound (e.g., a bear).
• An is used for words that begin with a vowel sound (e.g., an eagle).

Indefinite articles can only be used with singular countable nouns . Like definite articles, they are a type of determiner .

Editing and proofreading are different steps in the process of revising a text.

Editing comes first, and can involve major changes to content, structure and language. The first stages of editing are often done by authors themselves, while a professional editor makes the final improvements to grammar and style (for example, by improving sentence structure and word choice ).

Proofreading is the final stage of checking a text before it is published or shared. It focuses on correcting minor errors and inconsistencies (for example, in punctuation and capitalization ). Proofreaders often also check for formatting issues, especially in print publishing.

Whether you’re publishing a blog, submitting a research paper , or even just writing an important email, there are a few techniques you can use to make sure it’s error-free:

• Take a break : Set your work aside for at least a few hours so that you can look at it with fresh eyes.
• Proofread a printout : Staring at a screen for too long can cause fatigue – sit down with a pen and paper to check the final version.
• Use digital shortcuts : Take note of any recurring mistakes (for example, misspelling a particular word, switching between US and UK English , or inconsistently capitalizing a term), and use Find and Replace to fix it throughout the document.

If you want to be confident that an important text is error-free, it might be worth choosing a professional proofreading service instead.

There are many different routes to becoming a professional proofreader or editor. The necessary qualifications depend on the field – to be an academic or scientific proofreader, for example, you will need at least a university degree in a relevant subject.

For most proofreading jobs, experience and demonstrated skills are more important than specific qualifications. Often your skills will be tested as part of the application process.

To learn practical proofreading skills, you can choose to take a course with a professional organisation such as the Society for Editors and Proofreaders . Alternatively, you can apply to companies that offer specialised on-the-job training programmes, such as the Scribbr Academy .

Though they’re pronounced the same, there’s a big difference in meaning between its and it’s .

• ‘The cat ate its food’.
• ‘It’s almost Christmas’.

Its and it’s are often confused, but its (without apostrophe) is the possessive form of ‘it’ (e.g., its tail, its argument, its wing). You use ‘its’ instead of ‘his’ and ‘her’ for neuter, inanimate nouns.

Then and than are two commonly confused words with different meanings and grammatical roles.

• Then (pronounced with a short ‘e’ sound) refers to time. It’s often an adverb , but it can also be used as a noun meaning ‘that time’ and as an adjective referring to a previous status.
• Than (pronounced with a short ‘a’ sound) is used for comparisons. Grammatically, it usually functions as a conjunction , but sometimes it’s a preposition .

Use to and used to are commonly confused words . In the case of ‘used to be’, the latter (with ‘d’) is correct, since you’re describing an action or state in the past.

• I used to be the new coworker.
• There used to be 4 cookies left.
• We used to walk to school every day .

A grammar checker is a tool designed to automatically check your text for spelling errors, grammatical issues, punctuation mistakes , and problems with sentence structure . You can check out our analysis of the best free grammar checkers to learn more.

A paraphrasing tool edits your text more actively, changing things whether they were grammatically incorrect or not. It can paraphrase your sentences to make them more concise and readable or for other purposes. You can check out our analysis of the best free paraphrasing tools to learn more.

Some tools available online combine both functions. Others, such as QuillBot , have separate grammar checker and paraphrasing tools. Be aware of what exactly the tool you’re using does to avoid introducing unwanted changes.

Good grammar is the key to expressing yourself clearly and fluently, especially in professional communication and academic writing . Word processors, browsers, and email programs typically have built-in grammar checkers, but they’re quite limited in the kinds of problems they can fix.

If you want to go beyond detecting basic spelling errors, there are many online grammar checkers with more advanced functionality. They can often detect issues with punctuation , word choice, and sentence structure that more basic tools would miss.

Not all of these tools are reliable, though. You can check out our research into the best free grammar checkers to explore the options.

Our research indicates that the best free grammar checker available online is the QuillBot grammar checker .

We tested 10 of the most popular checkers with the same sample text (containing 20 grammatical errors) and found that QuillBot easily outperformed the competition, scoring 18 out of 20, a drastic improvement over the second-place score of 13 out of 20.

It even appeared to outperform the premium versions of other grammar checkers, despite being entirely free.

A teacher’s aide is a person who assists in teaching classes but is not a qualified teacher. Aide is a noun meaning ‘assistant’, so it will always refer to a person.

‘Teacher’s aid’ is incorrect.

A visual aid is an instructional device (e.g., a photo, a chart) that appeals to vision to help you understand written or spoken information. Aid is often placed after an attributive noun or adjective (like ‘visual’) that describes the type of help provided.

‘Visual aide’ is incorrect.

A job aid is an instructional tool (e.g., a checklist, a cheat sheet) that helps you work efficiently. Aid is a noun meaning ‘assistance’. It’s often placed after an adjective or attributive noun (like ‘job’) that describes the specific type of help provided.

‘Job aide’ is incorrect.

There are numerous synonyms for the various meanings of truly :

Yours truly is a phrase used at the end of a formal letter or email. It can also be used (typically in a humorous way) as a pronoun to refer to oneself (e.g., ‘The dinner was cooked by yours truly ‘). The latter usage should be avoided in formal writing.

It’s formed by combining the second-person possessive pronoun ‘yours’ with the adverb ‘ truly ‘.

A pathetic fallacy can be a short phrase or a whole sentence and is often used in novels and poetry. Pathetic fallacies serve multiple purposes, such as:

• Conveying the emotional state of the characters or the narrator
• Creating an atmosphere or set the mood of a scene
• Foreshadowing events to come
• Giving texture and vividness to a piece of writing
• Communicating emotion to the reader in a subtle way, by describing the external world.
• Bringing inanimate objects to life so that they seem more relatable.

AMA citation format is a citation style designed by the American Medical Association. It’s frequently used in the field of medicine.

You may be told to use AMA style for your student papers. You will also have to follow this style if you’re submitting a paper to a journal published by the AMA.

An AMA in-text citation consists of the number of the relevant reference on your AMA reference page , written in superscript 1 at the point in the text where the source is used.

It may also include the page number or range of the relevant material in the source (e.g., the part you quoted 2(p46) ). Multiple sources can be cited at one point, presented as a range or list (with no spaces 3,5–9 ).

An AMA reference usually includes the author’s last name and initials, the title of the source, information about the publisher or the publication it’s contained in, and the publication date. The specific details included, and the formatting, depend on the source type.

References in AMA style are presented in numerical order (numbered by the order in which they were first cited in the text) on your reference page. A source that’s cited repeatedly in the text still only appears once on the reference page.

An AMA in-text citation just consists of the number of the relevant entry on your AMA reference page , written in superscript at the point in the text where the source is referred to.

You don’t need to mention the author of the source in your sentence, but you can do so if you want. It’s not an official part of the citation, but it can be useful as part of a signal phrase introducing the source.

On your AMA reference page , author names are written with the last name first, followed by the initial(s) of their first name and middle name if mentioned.

There’s a space between the last name and the initials, but no space or punctuation between the initials themselves. The names of multiple authors are separated by commas , and the whole list ends in a period, e.g., ‘Andreessen F, Smith PW, Gonzalez E’.

The names of up to six authors should be listed for each source on your AMA reference page , separated by commas . For a source with seven or more authors, you should list the first three followed by ‘ et al’ : ‘Isidore, Gilbert, Gunvor, et al’.

In the text, mentioning author names is optional (as they aren’t an official part of AMA in-text citations ). If you do mention them, though, you should use the first author’s name followed by ‘et al’ when there are three or more : ‘Isidore et al argue that …’

Note that according to AMA’s rather minimalistic punctuation guidelines, there’s no period after ‘et al’ unless it appears at the end of a sentence. This is different from most other styles, where there is normally a period.

Yes, you should normally include an access date in an AMA website citation (or when citing any source with a URL). This is because webpages can change their content over time, so it’s useful for the reader to know when you accessed the page.

When a publication or update date is provided on the page, you should include it in addition to the access date. The access date appears second in this case, e.g., ‘Published June 19, 2021. Accessed August 29, 2022.’

Don’t include an access date when citing a source with a DOI (such as in an AMA journal article citation ).

Some variables have fixed levels. For example, gender and ethnicity are always nominal level data because they cannot be ranked.

However, for other variables, you can choose the level of measurement . For example, income is a variable that can be recorded on an ordinal or a ratio scale:

• At an ordinal level , you could create 5 income groupings and code the incomes that fall within them from 1–5.
• At a ratio level , you would record exact numbers for income.

If you have a choice, the ratio level is always preferable because you can analyse data in more ways. The higher the level of measurement, the more precise your data is.

The level at which you measure a variable determines how you can analyse your data.

Depending on the level of measurement , you can perform different descriptive statistics to get an overall summary of your data and inferential statistics to see if your results support or refute your hypothesis .

Levels of measurement tell you how precisely variables are recorded. There are 4 levels of measurement, which can be ranked from low to high:

• Nominal : the data can only be categorised.
• Ordinal : the data can be categorised and ranked.
• Interval : the data can be categorised and ranked, and evenly spaced.
• Ratio : the data can be categorised, ranked, evenly spaced and has a natural zero.

Statistical analysis is the main method for analyzing quantitative research data . It uses probabilities and models to test predictions about a population from sample data.

The null hypothesis is often abbreviated as H 0 . When the null hypothesis is written using mathematical symbols, it always includes an equality symbol (usually =, but sometimes ≥ or ≤).

The alternative hypothesis is often abbreviated as H a or H 1 . When the alternative hypothesis is written using mathematical symbols, it always includes an inequality symbol (usually ≠, but sometimes < or >).

As the degrees of freedom increase, Student’s t distribution becomes less leptokurtic , meaning that the probability of extreme values decreases. The distribution becomes more and more similar to a standard normal distribution .

When there are only one or two degrees of freedom , the chi-square distribution is shaped like a backwards ‘J’. When there are three or more degrees of freedom, the distribution is shaped like a right-skewed hump. As the degrees of freedom increase, the hump becomes less right-skewed and the peak of the hump moves to the right. The distribution becomes more and more similar to a normal distribution .

‘Looking forward in hearing from you’ is an incorrect version of the phrase looking forward to hearing from you . The phrasal verb ‘looking forward to’ always needs the preposition ‘to’, not ‘in’.

• I am looking forward in hearing from you.
• I am looking forward to hearing from you.

Some synonyms and near synonyms for the expression looking forward to hearing from you include:

• Eagerly awaiting your response
• Hoping to hear from you soon
• It would be great to hear back from you
• Thanks in advance for your reply

People sometimes mistakenly write ‘looking forward to hear from you’, but this is incorrect. The correct phrase is looking forward to hearing from you .

The phrasal verb ‘look forward to’ is always followed by a direct object, the thing you’re looking forward to. As the direct object has to be a noun phrase , it should be the gerund ‘hearing’, not the verb ‘hear’.

• I’m looking forward to hear from you soon.
• I’m looking forward to hearing from you soon.

Traditionally, the sign-off Yours sincerely is used in an email message or letter when you are writing to someone you have interacted with before, not a complete stranger.

Yours faithfully is used instead when you are writing to someone you have had no previous correspondence with, especially if you greeted them as ‘ Dear Sir or Madam ’.

Just checking in   is a standard phrase used to start an email (or other message) that’s intended to ask someone for a response or follow-up action in a friendly, informal way. However, it’s a cliché opening that can come across as passive-aggressive, so we recommend avoiding it in favor of a more direct opening like “We previously discussed …”

In a more personal context, you might encounter “just checking in” as part of a longer phrase such as “I’m just checking in to see how you’re doing”. In this case, it’s not asking the other person to do anything but rather asking about their well-being (emotional or physical) in a friendly way.

“Earliest convenience” is part of the phrase at your earliest convenience , meaning “as soon as you can”. 

It’s typically used to end an email in a formal context by asking the recipient to do something when it’s convenient for them to do so.

ASAP is an abbreviation of the phrase “as soon as possible”. 

It’s typically used to indicate a sense of urgency in highly informal contexts (e.g., “Let me know ASAP if you need me to drive you to the airport”).

“ASAP” should be avoided in more formal correspondence. Instead, use an alternative like at your earliest convenience .

Some synonyms and near synonyms of the verb   compose   (meaning “to make up”) are:

People increasingly use “comprise” as a synonym of “compose.” However, this is normally still seen as a mistake, and we recommend avoiding it in your academic writing . “Comprise” traditionally means “to be made up of,” not “to make up.”

Some synonyms and near synonyms of the verb comprise are:

• Be composed of
• Be made up of

People increasingly use “comprise” interchangeably with “compose,” meaning that they consider words like “compose,” “constitute,” and “form” to be synonymous with “comprise.” However, this is still normally regarded as an error, and we advise against using these words interchangeably in academic writing .

A fallacy is a mistaken belief, particularly one based on unsound arguments or one that lacks the evidence to support it. Common types of fallacy that may compromise the quality of your research are:

• Correlation/causation fallacy: Claiming that two events that occur together have a cause-and-effect relationship even though this can’t be proven
• Ecological fallacy : Making inferences about the nature of individuals based on aggregate data for the group
• The sunk cost fallacy : Following through on a project or decision because we have already invested time, effort, or money into it, even if the current costs outweigh the benefits
• The base-rate fallacy : Ignoring base-rate or statistically significant information, such as sample size or the relative frequency of an event, in favor of  less relevant information e.g., pertaining to a single case, or a small number of cases
• The planning fallacy : Underestimating the time needed to complete a future task, even when we know that similar tasks in the past have taken longer than planned

The planning fallacy refers to people’s tendency to underestimate the resources needed to complete a future task, despite knowing that previous tasks have also taken longer than planned.

For example, people generally tend to underestimate the cost and time needed for construction projects. The planning fallacy occurs due to people’s tendency to overestimate the chances that positive events, such as a shortened timeline, will happen to them. This phenomenon is called optimism bias or positivity bias.

Although both red herring fallacy and straw man fallacy are logical fallacies or reasoning errors, they denote different attempts to “win” an argument. More specifically:

• A red herring fallacy refers to an attempt to change the subject and divert attention from the original issue. In other words, a seemingly solid but ultimately irrelevant argument is introduced into the discussion, either on purpose or by mistake.
• A straw man argument involves the deliberate distortion of another person’s argument. By oversimplifying or exaggerating it, the other party creates an easy-to-refute argument and then attacks it.

The red herring fallacy is a problem because it is flawed reasoning. It is a distraction device that causes people to become sidetracked from the main issue and draw wrong conclusions.

Although a red herring may have some kernel of truth, it is used as a distraction to keep our eyes on a different matter. As a result, it can cause us to accept and spread misleading information.

The sunk cost fallacy and escalation of commitment (or commitment bias ) are two closely related terms. However, there is a slight difference between them:

• Escalation of commitment (aka commitment bias ) is the tendency to be consistent with what we have already done or said we will do in the past, especially if we did so in public. In other words, it is an attempt to save face and appear consistent.
• Sunk cost fallacy is the tendency to stick with a decision or a plan even when it’s failing. Because we have already invested valuable time, money, or energy, quitting feels like these resources were wasted.

In other words, escalating commitment is a manifestation of the sunk cost fallacy: an irrational escalation of commitment frequently occurs when people refuse to accept that the resources they’ve already invested cannot be recovered. Instead, they insist on more spending to justify the initial investment (and the incurred losses).

When you are faced with a straw man argument , the best way to respond is to draw attention to the fallacy and ask your discussion partner to show how your original statement and their distorted version are the same. Since these are different, your partner will either have to admit that their argument is invalid or try to justify it by using more flawed reasoning, which you can then attack.

The straw man argument is a problem because it occurs when we fail to take an opposing point of view seriously. Instead, we intentionally misrepresent our opponent’s ideas and avoid genuinely engaging with them. Due to this, resorting to straw man fallacy lowers the standard of constructive debate.

A straw man argument is a distorted (and weaker) version of another person’s argument that can easily be refuted (e.g., when a teacher proposes that the class spend more time on math exercises, a parent complains that the teacher doesn’t care about reading and writing).

This is a straw man argument because it misrepresents the teacher’s position, which didn’t mention anything about cutting down on reading and writing. The straw man argument is also known as the straw man fallacy .

A slippery slope argument is not always a fallacy.

• When someone claims adopting a certain policy or taking a certain action will automatically lead to a series of other policies or actions also being taken, this is a slippery slope argument.
• If they don’t show a causal connection between the advocated policy and the consequent policies, then they commit a slippery slope fallacy .

There are a number of ways you can deal with slippery slope arguments especially when you suspect these are fallacious:

• Slippery slope arguments take advantage of the gray area between an initial action or decision and the possible next steps that might lead to the undesirable outcome. You can point out these missing steps and ask your partner to indicate what evidence exists to support the claimed relationship between two or more events.
• Ask yourself if each link in the chain of events or action is valid. Every proposition has to be true for the overall argument to work, so even if one link is irrational or not supported by evidence, then the argument collapses.
• Sometimes people commit a slippery slope fallacy unintentionally. In these instances, use an example that demonstrates the problem with slippery slope arguments in general (e.g., by using statements to reach a conclusion that is not necessarily relevant to the initial statement). By attacking the concept of slippery slope arguments you can show that they are often fallacious.

People sometimes confuse cognitive bias and logical fallacies because they both relate to flawed thinking. However, they are not the same:

• Cognitive bias is the tendency to make decisions or take action in an illogical way because of our values, memory, socialization, and other personal attributes. In other words, it refers to a fixed pattern of thinking rooted in the way our brain works.
• Logical fallacies relate to how we make claims and construct our arguments in the moment. They are statements that sound convincing at first but can be disproven through logical reasoning.

In other words, cognitive bias refers to an ongoing predisposition, while logical fallacy refers to mistakes of reasoning that occur in the moment.

An appeal to ignorance (ignorance here meaning lack of evidence) is a type of informal logical fallacy .

It asserts that something must be true because it hasn’t been proven false—or that something must be false because it has not yet been proven true.

For example, “unicorns exist because there is no evidence that they don’t.” The appeal to ignorance is also called the burden of proof fallacy .

An ad hominem (Latin for “to the person”) is a type of informal logical fallacy . Instead of arguing against a person’s position, an ad hominem argument attacks the person’s character or actions in an effort to discredit them.

This rhetorical strategy is fallacious because a person’s character, motive, education, or other personal trait is logically irrelevant to whether their argument is true or false.

Name-calling is common in ad hominem fallacy (e.g., “environmental activists are ineffective because they’re all lazy tree-huggers”).

Ad hominem is a persuasive technique where someone tries to undermine the opponent’s argument by personally attacking them.

In this way, one can redirect the discussion away from the main topic and to the opponent’s personality without engaging with their viewpoint. When the opponent’s personality is irrelevant to the discussion, we call it an ad hominem fallacy .

Ad hominem tu quoque (‘you too”) is an attempt to rebut a claim by attacking its proponent on the grounds that they uphold a double standard or that they don’t practice what they preach. For example, someone is telling you that you should drive slowly otherwise you’ll get a speeding ticket one of these days, and you reply “but you used to get them all the time!”

Argumentum ad hominem means “argument to the person” in Latin and it is commonly referred to as ad hominem argument or personal attack. Ad hominem arguments are used in debates to refute an argument by attacking the character of the person making it, instead of the logic or premise of the argument itself.

The opposite of the hasty generalization fallacy is called slothful induction fallacy or appeal to coincidence .

It is the tendency to deny a conclusion even though there is sufficient evidence that supports it. Slothful induction occurs due to our natural tendency to dismiss events or facts that do not align with our personal biases and expectations. For example, a researcher may try to explain away unexpected results by claiming it is just a coincidence.

To avoid a hasty generalization fallacy we need to ensure that the conclusions drawn are well-supported by the appropriate evidence. More specifically:

• In statistics , if we want to draw inferences about an entire population, we need to make sure that the sample is random and representative of the population . We can achieve that by using a probability sampling method , like simple random sampling or stratified sampling .
• In academic writing , use precise language and measured phases. Try to avoid making absolute claims, cite specific instances and examples without applying the findings to a larger group.
• As readers, we need to ask ourselves “does the writer demonstrate sufficient knowledge of the situation or phenomenon that would allow them to make a generalization?”

The hasty generalization fallacy and the anecdotal evidence fallacy are similar in that they both result in conclusions drawn from insufficient evidence. However, there is a difference between the two:

• The hasty generalization fallacy involves genuinely considering an example or case (i.e., the evidence comes first and then an incorrect conclusion is drawn from this).
• The anecdotal evidence fallacy (also known as “cherry-picking” ) is knowing in advance what conclusion we want to support, and then selecting the story (or a few stories) that support it. By overemphasizing anecdotal evidence that fits well with the point we are trying to make, we overlook evidence that would undermine our argument.

Although many sources use circular reasoning fallacy and begging the question interchangeably, others point out that there is a subtle difference between the two:

• Begging the question fallacy occurs when you assume that an argument is true in order to justify a conclusion. If something begs the question, what you are actually asking is, “Is the premise of that argument actually true?” For example, the statement “Snakes make great pets. That’s why we should get a snake” begs the question “are snakes really great pets?”
• Circular reasoning fallacy on the other hand, occurs when the evidence used to support a claim is just a repetition of the claim itself.  For example, “People have free will because they can choose what to do.”

In other words, we could say begging the question is a form of circular reasoning.

Circular reasoning fallacy uses circular reasoning to support an argument. More specifically, the evidence used to support a claim is just a repetition of the claim itself. For example: “The President of the United States is a good leader (claim), because they are the leader of this country (supporting evidence)”.

An example of a non sequitur is the following statement:

“Giving up nuclear weapons weakened the United States’ military. Giving up nuclear weapons also weakened China. For this reason, it is wrong to try to outlaw firearms in the United States today.”

Clearly there is a step missing in this line of reasoning and the conclusion does not follow from the premise, resulting in a non sequitur fallacy .

The difference between the post hoc fallacy and the non sequitur fallacy is that post hoc fallacy infers a causal connection between two events where none exists, whereas the non sequitur fallacy infers a conclusion that lacks a logical connection to the premise.

In other words, a post hoc fallacy occurs when there is a lack of a cause-and-effect relationship, while a non sequitur fallacy occurs when there is a lack of logical connection.

An example of post hoc fallacy is the following line of reasoning:

“Yesterday I had ice cream, and today I have a terrible stomachache. I’m sure the ice cream caused this.”

Although it is possible that the ice cream had something to do with the stomachache, there is no proof to justify the conclusion other than the order of events. Therefore, this line of reasoning is fallacious.

Post hoc fallacy and hasty generalisation fallacy are similar in that they both involve jumping to conclusions. However, there is a difference between the two:

• Post hoc fallacy is assuming a cause and effect relationship between two events, simply because one happened after the other.
• Hasty generalisation fallacy is drawing a general conclusion from a small sample or little evidence.

In other words, post hoc fallacy involves a leap to a causal claim; hasty generalisation fallacy involves a leap to a general proposition.

The fallacy of composition is similar to and can be confused with the hasty generalization fallacy . However, there is a difference between the two:

• The fallacy of composition involves drawing an inference about the characteristics of a whole or group based on the characteristics of its individual members.
• The hasty generalization fallacy involves drawing an inference about a population or class of things on the basis of few atypical instances or a small sample of that population or thing.

In other words, the fallacy of composition is using an unwarranted assumption that we can infer something about a whole based on the characteristics of its parts, while the hasty generalization fallacy is using insufficient evidence to draw a conclusion.

The opposite of the fallacy of composition is the fallacy of division . In the fallacy of division, the assumption is that a characteristic which applies to a whole or a group must necessarily apply to the parts or individual members. For example, “Australians travel a lot. Gary is Australian, so he must travel a lot.”

Base rate fallacy can be avoided by following these steps:

• Avoid making an important decision in haste. When we are under pressure, we are more likely to resort to cognitive shortcuts like the availability heuristic and the representativeness heuristic . Due to this, we are more likely to factor in only current and vivid information, and ignore the actual probability of something happening (i.e., base rate).
• Take a long-term view on the decision or question at hand. Look for relevant statistical data, which can reveal long-term trends and give you the full picture.
• Talk to experts like professionals. They are more aware of probabilities related to specific decisions.

Suppose there is a population consisting of 90% psychologists and 10% engineers. Given that you know someone enjoyed physics at school, you may conclude that they are an engineer rather than a psychologist, even though you know that this person comes from a population consisting of far more psychologists than engineers.

When we ignore the rate of occurrence of some trait in a population (the base-rate information) we commit base rate fallacy .

Cost-benefit fallacy is a common error that occurs when allocating sources in project management. It is the fallacy of assuming that cost-benefit estimates are more or less accurate, when in fact they are highly inaccurate and biased. This means that cost-benefit analyses can be useful, but only after the cost-benefit fallacy has been acknowledged and corrected for. Cost-benefit fallacy is a type of base rate fallacy .

In advertising, the fallacy of equivocation is often used to create a pun. For example, a billboard company might advertise their billboards using a line like: “Looking for a sign? This is it!” The word sign has a literal meaning as billboard and a figurative one as a sign from God, the universe, etc.

Equivocation is a fallacy because it is a form of argumentation that is both misleading and logically unsound. When the meaning of a word or phrase shifts in the course of an argument, it causes confusion and also implies that the conclusion (which may be true) does not follow from the premise.

The fallacy of equivocation is an informal logical fallacy, meaning that the error lies in the content of the argument instead of the structure.

Fallacies of relevance are a group of fallacies that occur in arguments when the premises are logically irrelevant to the conclusion. Although at first there seems to be a connection between the premise and the conclusion, in reality fallacies of relevance use unrelated forms of appeal.

For example, the genetic fallacy makes an appeal to the source or origin of the claim in an attempt to assert or refute something.

The ad hominem fallacy and the genetic fallacy are closely related in that they are both fallacies of relevance. In other words, they both involve arguments that use evidence or examples that are not logically related to the argument at hand. However, there is a difference between the two:

• In the ad hominem fallacy , the goal is to discredit the argument by discrediting the person currently making the argument.
• In the genetic fallacy , the goal is to discredit the argument by discrediting the history or origin (i.e., genesis) of an argument.

False dilemma fallacy is also known as false dichotomy, false binary, and “either-or” fallacy. It is the fallacy of presenting only two choices, outcomes, or sides to an argument as the only possibilities, when more are available.

The false dilemma fallacy works in two ways:

• By presenting only two options as if these were the only ones available
• By presenting two options as mutually exclusive (i.e., only one option can be selected or can be true at a time)

In both cases, by using the false dilemma fallacy, one conceals alternative choices and doesn’t allow others to consider the full range of options. This is usually achieved through an“either-or” construction and polarised, divisive language (“you are either a friend or an enemy”).

The best way to avoid a false dilemma fallacy is to pause and reflect on two points:

• Are the options presented truly the only ones available ? It could be that another option has been deliberately omitted.
• Are the options mentioned mutually exclusive ? Perhaps all of the available options can be selected (or be true) at the same time, which shows that they aren’t mutually exclusive. Proving this is called “escaping between the horns of the dilemma.”

Begging the question fallacy is an argument in which you assume what you are trying to prove. In other words, your position and the justification of that position are the same, only slightly rephrased.

For example: “All freshmen should attend college orientation, because all college students should go to such an orientation.”

The complex question fallacy and begging the question fallacy are similar in that they are both based on assumptions. However, there is a difference between them:

• A complex question fallacy occurs when someone asks a question that presupposes the answer to another question that has not been established or accepted by the other person. For example, asking someone “Have you stopped cheating on tests?”, unless it has previously been established that the person is indeed cheating on tests, is a fallacy.
• Begging the question fallacy occurs when we assume the very thing as a premise that we’re trying to prove in our conclusion. In other words, the conclusion is used to support the premises, and the premises prove the validity of the conclusion. For example: “God exists because the Bible says so, and the Bible is true because it is the word of God.”

In other words, begging the question is about drawing a conclusion based on an assumption, while a complex question involves asking a question that presupposes the answer to a prior question.

“ No true Scotsman ” arguments aren’t always fallacious. When there is a generally accepted definition of who or what constitutes a group, it’s reasonable to use statements in the form of “no true Scotsman”.

For example, the statement that “no true pacifist would volunteer for military service” is not fallacious, since a pacifist is, by definition, someone who opposes war or violence as a means of settling disputes.

No true Scotsman arguments are fallacious because instead of logically refuting the counterexample, they simply assert that it doesn’t count. In other words, the counterexample is rejected for psychological, but not logical, reasons.

The appeal to purity or no true Scotsman fallacy is an attempt to defend a generalisation about a group from a counterexample by shifting the definition of the group in the middle of the argument. In this way, one can exclude the counterexample as not being “true”, “genuine”, or “pure” enough to be considered as part of the group in question.

To identify an appeal to authority fallacy , you can ask yourself the following questions:

• Is the authority cited really a qualified expert in this particular area under discussion? For example, someone who has formal education or years of experience can be an expert.
• Do experts disagree on this particular subject? If that is the case, then for almost any claim supported by one expert there will be a counterclaim that is supported by another expert. If there is no consensus, an appeal to authority is fallacious.
• Is the authority in question biased? If you suspect that an expert’s prejudice and bias could have influenced their views, then the expert is not reliable and an argument citing this expert will be fallacious.To identify an appeal to authority fallacy, you ask yourself whether the authority cited is a qualified expert in the particular area under discussion.

Appeal to authority is a fallacy when those who use it do not provide any justification to support their argument. Instead they cite someone famous who agrees with their viewpoint, but is not qualified to make reliable claims on the subject.

Appeal to authority fallacy is often convincing because of the effect authority figures have on us. When someone cites a famous person, a well-known scientist, a politician, etc. people tend to be distracted and often fail to critically examine whether the authority figure is indeed an expert in the area under discussion.

The ad populum fallacy is common in politics. One example is the following viewpoint: “The majority of our countrymen think we should have military operations overseas; therefore, it’s the right thing to do.”

This line of reasoning is fallacious, because popular acceptance of a belief or position does not amount to a justification of that belief. In other words, following the prevailing opinion without examining the underlying reasons is irrational.

The ad populum fallacy plays on our innate desire to fit in (known as “bandwagon effect”). If many people believe something, our common sense tells us that it must be true and we tend to accept it. However, in logic, the popularity of a proposition cannot serve as evidence of its truthfulness.

Ad populum (or appeal to popularity) fallacy and appeal to authority fallacy are similar in that they both conflate the validity of a belief with its popular acceptance among a specific group. However there is a key difference between the two:

• An ad populum fallacy tries to persuade others by claiming that something is true or right because a lot of people think so.
• An appeal to authority fallacy tries to persuade by claiming a group of experts believe something is true or right, therefore it must be so.

To identify a false cause fallacy , you need to carefully analyse the argument:

• When someone claims that one event directly causes another, ask if there is sufficient evidence to establish a cause-and-effect relationship. 
• Ask if the claim is based merely on the chronological order or co-occurrence of the two events. 
• Consider alternative possible explanations (are there other factors at play that could influence the outcome?).

By carefully analysing the reasoning, considering alternative explanations, and examining the evidence provided, you can identify a false cause fallacy and discern whether a causal claim is valid or flawed.

False cause fallacy examples include: 

• Believing that wearing your lucky jersey will help your team win 
• Thinking that everytime you wash your car, it rains
• Claiming that playing video games causes violent behavior 

In each of these examples, we falsely assume that one event causes another without any proof.

The planning fallacy and procrastination are not the same thing. Although they both relate to time and task management, they describe different challenges:

• The planning fallacy describes our inability to correctly estimate how long a future task will take, mainly due to optimism bias and a strong focus on the best-case scenario.
• Procrastination refers to postponing a task, usually by focusing on less urgent or more enjoyable activities. This is due to psychological reasons, like fear of failure.

In other words, the planning fallacy refers to inaccurate predictions about the time we need to finish a task, while procrastination is a deliberate delay due to psychological factors.

A real-life example of the planning fallacy is the construction of the Sydney Opera House in Australia. When construction began in the late 1950s, it was initially estimated that it would be completed in four years at a cost of around $7 million.

Because the government wanted the construction to start before political opposition would stop it and while public opinion was still favorable, a number of design issues had not been carefully studied in advance. Due to this, several problems appeared immediately after the project commenced.

The construction process eventually stretched over 14 years, with the Opera House being completed in 1973 at a cost of over $100 million, significantly exceeding the initial estimates.

An example of appeal to pity fallacy is the following appeal by a student to their professor:

“Professor, please consider raising my grade. I had a terrible semester: my car broke down, my laptop got stolen, and my cat got sick.”

While these circumstances may be unfortunate, they are not directly related to the student’s academic performance.

While both the appeal to pity fallacy and   red herring fallacy can serve as a distraction from the original discussion topic, they are distinct fallacies. More specifically:

• Appeal to pity fallacy attempts to evoke feelings of sympathy, pity, or guilt in an audience, so that they accept the speaker’s conclusion as truthful.
• Red herring fallacy attempts to introduce an irrelevant piece of information that diverts the audience’s attention to a different topic.

Both fallacies can be used as a tool of deception. However, they operate differently and serve distinct purposes in arguments.

Argumentum ad misericordiam (Latin for “argument from pity or misery”) is another name for appeal to pity fallacy . It occurs when someone evokes sympathy or guilt in an attempt to gain support for their claim, without providing any logical reasons to support the claim itself. Appeal to pity is a deceptive tactic of argumentation, playing on people’s emotions to sway their opinion.

Yes, it’s quite common to start a sentence with a preposition, and there’s no reason not to do so.

For example, the sentence “ To many, she was a hero” is perfectly grammatical. It could also be rephrased as “She was a hero to  many”, but there’s no particular reason to do so. Both versions are fine.

Some people argue that you shouldn’t end a sentence with a preposition , but that “rule” can also be ignored, since it’s not supported by serious language authorities.

Yes, it’s fine to end a sentence with a preposition . The “rule” against doing so is overwhelmingly rejected by modern style guides and language authorities and is based on the rules of Latin grammar, not English.

Trying to avoid ending a sentence with a preposition often results in very unnatural phrasings. For example, turning “He knows what he’s talking about ” into “He knows about what he’s talking” or “He knows that about which he’s talking” is definitely not an improvement.

No, ChatGPT is not a credible source of factual information and can’t be cited for this purpose in academic writing . While it tries to provide accurate answers, it often gets things wrong because its responses are based on patterns, not facts and data.

Specifically, the CRAAP test for evaluating sources includes five criteria: currency , relevance , authority , accuracy , and purpose . ChatGPT fails to meet at least three of them:

• Currency: The dataset that ChatGPT was trained on only extends to 2021, making it slightly outdated.
• Authority: It’s just a language model and is not considered a trustworthy source of factual information.
• Accuracy: It bases its responses on patterns rather than evidence and is unable to cite its sources .

So you shouldn’t cite ChatGPT as a trustworthy source for a factual claim. You might still cite ChatGPT for other reasons – for example, if you’re writing a paper about AI language models, ChatGPT responses are a relevant primary source .

ChatGPT is an AI language model that was trained on a large body of text from a variety of sources (e.g., Wikipedia, books, news articles, scientific journals). The dataset only went up to 2021, meaning that it lacks information on more recent events.

It’s also important to understand that ChatGPT doesn’t access a database of facts to answer your questions. Instead, its responses are based on patterns that it saw in the training data.

So ChatGPT is not always trustworthy . It can usually answer general knowledge questions accurately, but it can easily give misleading answers on more specialist topics.

Another consequence of this way of generating responses is that ChatGPT usually can’t cite its sources accurately. It doesn’t really know what source it’s basing any specific claim on. It’s best to check any information you get from it against a credible source .

No, it is not possible to cite your sources with ChatGPT . You can ask it to create citations, but it isn’t designed for this task and tends to make up sources that don’t exist or present information in the wrong format. ChatGPT also cannot add citations to direct quotes in your text.

Instead, use a tool designed for this purpose, like the Scribbr Citation Generator .

But you can use ChatGPT for assignments in other ways, to provide inspiration, feedback, and general writing advice.

GPT  stands for “generative pre-trained transformer”, which is a type of large language model: a neural network trained on a very large amount of text to produce convincing, human-like language outputs. The Chat part of the name just means “chat”: ChatGPT is a chatbot that you interact with by typing in text.

The technology behind ChatGPT is GPT-3.5 (in the free version) or GPT-4 (in the premium version). These are the names for the specific versions of the GPT model. GPT-4 is currently the most advanced model that OpenAI has created. It’s also the model used in Bing’s chatbot feature.

ChatGPT was created by OpenAI, an AI research company. It started as a nonprofit company in 2015 but became for-profit in 2019. Its CEO is Sam Altman, who also co-founded the company. OpenAI released ChatGPT as a free “research preview” in November 2022. Currently, it’s still available for free, although a more advanced premium version is available if you pay for it.

OpenAI is also known for developing DALL-E, an AI image generator that runs on similar technology to ChatGPT.

ChatGPT is owned by OpenAI, the company that developed and released it. OpenAI is a company dedicated to AI research. It started as a nonprofit company in 2015 but transitioned to for-profit in 2019. Its current CEO is Sam Altman, who also co-founded the company.

In terms of who owns the content generated by ChatGPT, OpenAI states that it will not claim copyright on this content , and the terms of use state that “you can use Content for any purpose, including commercial purposes such as sale or publication”. This means that you effectively own any content you generate with ChatGPT and can use it for your own purposes.

Be cautious about how you use ChatGPT content in an academic context. University policies on AI writing are still developing, so even if you “own” the content, you’re often not allowed to submit it as your own work according to your university or to publish it in a journal.

ChatGPT is a chatbot based on a large language model (LLM). These models are trained on huge datasets consisting of hundreds of billions of words of text, based on which the model learns to effectively predict natural responses to the prompts you enter.

ChatGPT was also refined through a process called reinforcement learning from human feedback (RLHF), which involves “rewarding” the model for providing useful answers and discouraging inappropriate answers – encouraging it to make fewer mistakes.

Essentially, ChatGPT’s answers are based on predicting the most likely responses to your inputs based on its training data, with a reward system on top of this to incentivise it to give you the most helpful answers possible. It’s a bit like an incredibly advanced version of predictive text. This is also one of ChatGPT’s limitations : because its answers are based on probabilities, they’re not always trustworthy .

OpenAI may store ChatGPT conversations for the purposes of future training. Additionally, these conversations may be monitored by human AI trainers.

Users can choose not to have their chat history saved. Unsaved chats are not used to train future models and are permanently deleted from ChatGPT’s system after 30 days.

The official ChatGPT app is currently only available on iOS devices. If you don’t have an iOS device, only use the official OpenAI website to access the tool. This helps to eliminate the potential risk of downloading fraudulent or malicious software.

ChatGPT conversations are generally used to train future models and to resolve issues/bugs. These chats may be monitored by human AI trainers.

However, users can opt out of having their conversations used for training. In these instances, chats are monitored only for potential abuse.

Yes, using ChatGPT as a conversation partner is a great way to practice a language in an interactive way.

Try using a prompt like this one:

“Please be my Spanish conversation partner. Only speak to me in Spanish. Keep your answers short (maximum 50 words). Ask me questions. Let’s start the conversation with the following topic: [conversation topic].”

Yes, there are a variety of ways to use ChatGPT for language learning , including treating it as a conversation partner, asking it for translations, and using it to generate a curriculum or practice exercises.

AI detectors aim to identify the presence of AI-generated text (e.g., from ChatGPT ) in a piece of writing, but they can’t do so with complete accuracy. In our comparison of the best AI detectors , we found that the 10 tools we tested had an average accuracy of 60%. The best free tool had 68% accuracy, the best premium tool 84%.

Because of how AI detectors work , they can never guarantee 100% accuracy, and there is always at least a small risk of false positives (human text being marked as AI-generated). Therefore, these tools should not be relied upon to provide absolute proof that a text is or isn’t AI-generated. Rather, they can provide a good indication in combination with other evidence.

Tools called AI detectors are designed to label text as AI-generated or human. AI detectors work by looking for specific characteristics in the text, such as a low level of randomness in word choice and sentence length. These characteristics are typical of AI writing, allowing the detector to make a good guess at when text is AI-generated.

But these tools can’t guarantee 100% accuracy. Check out our comparison of the best AI detectors to learn more.

You can also manually watch for clues that a text is AI-generated – for example, a very different style from the writer’s usual voice or a generic, overly polite tone.

Our research into the best summary generators (aka summarisers or summarising tools) found that the best summariser available in 2023 is the one offered by QuillBot.

While many summarisers just pick out some sentences from the text, QuillBot generates original summaries that are creative, clear, accurate, and concise. It can summarise texts of up to 1,200 words for free, or up to 6,000 with a premium subscription.

Try the QuillBot summarizer for free

Deep learning requires a large dataset (e.g., images or text) to learn from. The more diverse and representative the data, the better the model will learn to recognise objects or make predictions. Only when the training data is sufficiently varied can the model make accurate predictions or recognise objects from new data.

Deep learning models can be biased in their predictions if the training data consist of biased information. For example, if a deep learning model used for screening job applicants has been trained with a dataset consisting primarily of white male applicants, it will consistently favour this specific population over others.

A good ChatGPT prompt (i.e., one that will get you the kinds of responses you want):

• Gives the tool a role to explain what type of answer you expect from it
• Is precisely formulated and gives enough context
• Is free from bias
• Has been tested and improved by experimenting with the tool

ChatGPT prompts are the textual inputs (e.g., questions, instructions) that you enter into ChatGPT to get responses.

ChatGPT predicts an appropriate response to the prompt you entered. In general, a more specific and carefully worded prompt will get you better responses.

Yes, ChatGPT is currently available for free. You have to sign up for a free account to use the tool, and you should be aware that your data may be collected to train future versions of the model.

To sign up and use the tool for free, go to this page and click “Sign up”. You can do so with your email or with a Google account.

A premium version of the tool called ChatGPT Plus is available as a monthly subscription. It currently costs £16 and gets you access to features like GPT-4 (a more advanced version of the language model). But it’s optional: you can use the tool completely free if you’re not interested in the extra features.

You can access ChatGPT by signing up for a free account:

• Follow this link to the ChatGPT website.
• Click on “Sign up” and fill in the necessary details (or use your Google account). It’s free to sign up and use the tool.
• Type a prompt into the chat box to get started!

A ChatGPT app is also available for iOS, and an Android app is planned for the future. The app works similarly to the website, and you log in with the same account for both.

According to OpenAI’s terms of use, users have the right to reproduce text generated by ChatGPT during conversations.

However, publishing ChatGPT outputs may have legal implications , such as copyright infringement.

Users should be aware of such issues and use ChatGPT outputs as a source of inspiration instead.

According to OpenAI’s terms of use, users have the right to use outputs from their own ChatGPT conversations for any purpose (including commercial publication).

However, users should be aware of the potential legal implications of publishing ChatGPT outputs. ChatGPT responses are not always unique: different users may receive the same response.

Furthermore, ChatGPT outputs may contain copyrighted material. Users may be liable if they reproduce such material.

ChatGPT can sometimes reproduce biases from its training data , since it draws on the text it has “seen” to create plausible responses to your prompts.

For example, users have shown that it sometimes makes sexist assumptions such as that a doctor mentioned in a prompt must be a man rather than a woman. Some have also pointed out political bias in terms of which political figures the tool is willing to write positively or negatively about and which requests it refuses.

The tool is unlikely to be consistently biased toward a particular perspective or against a particular group. Rather, its responses are based on its training data and on the way you phrase your ChatGPT prompts . It’s sensitive to phrasing, so asking it the same question in different ways will result in quite different answers.

Information extraction  refers to the process of starting from unstructured sources (e.g., text documents written in ordinary English) and automatically extracting structured information (i.e., data in a clearly defined format that’s easily understood by computers). It’s an important concept in natural language processing (NLP) .

For example, you might think of using news articles full of celebrity gossip to automatically create a database of the relationships between the celebrities mentioned (e.g., married, dating, divorced, feuding). You would end up with data in a structured format, something like MarriageBetween(celebrity 1 ,celebrity 2 ,date) .

The challenge involves developing systems that can “understand” the text well enough to extract this kind of data from it.

Knowledge representation and reasoning (KRR) is the study of how to represent information about the world in a form that can be used by a computer system to solve and reason about complex problems. It is an important field of artificial intelligence (AI) research.

An example of a KRR application is a semantic network, a way of grouping words or concepts by how closely related they are and formally defining the relationships between them so that a machine can “understand” language in something like the way people do.

A related concept is information extraction , concerned with how to get structured information from unstructured sources.

Yes, you can use ChatGPT to summarise text . This can help you understand complex information more easily, summarise the central argument of your own paper, or clarify your research question.

You can also use Scribbr’s free text summariser , which is designed specifically for this purpose.

Yes, you can use ChatGPT to paraphrase text to help you express your ideas more clearly, explore different ways of phrasing your arguments, and avoid repetition.

However, it’s not specifically designed for this purpose. We recommend using a specialised tool like Scribbr’s free paraphrasing tool , which will provide a smoother user experience.

Yes, you use ChatGPT to help write your college essay by having it generate feedback on certain aspects of your work (consistency of tone, clarity of structure, etc.).

However, ChatGPT is not able to adequately judge qualities like vulnerability and authenticity. For this reason, it’s important to also ask for feedback from people who have experience with college essays and who know you well. Alternatively, you can get advice using Scribbr’s essay editing service .

No, having ChatGPT write your college essay can negatively impact your application in numerous ways. ChatGPT outputs are unoriginal and lack personal insight.

Furthermore, Passing off AI-generated text as your own work is considered academically dishonest . AI detectors may be used to detect this offense, and it’s highly unlikely that any university will accept you if you are caught submitting an AI-generated admission essay.

However, you can use ChatGPT to help write your college essay during the preparation and revision stages (e.g., for brainstorming ideas and generating feedback).

ChatGPT and other AI writing tools can have unethical uses. These include:

• Reproducing biases and false information
• Using ChatGPT to cheat in academic contexts
• Violating the privacy of others by inputting personal information

However, when used correctly, AI writing tools can be helpful resources for improving your academic writing and research skills. Some ways to use ChatGPT ethically include:

• Following your institution’s guidelines
• Critically evaluating outputs
• Being transparent about how you used the tool

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Sat / act prep online guides and tips, the best college essay length: how long should it be.

College Essays

Figuring out your college essay can be one of the most difficult parts of applying to college. Even once you've read the prompt and picked a topic, you might wonder: if you write too much or too little, will you blow your chance of admission? How long should a college essay be?

Whether you're a terse writer or a loquacious one, we can advise you on college essay length. In this guide, we'll cover what the standard college essay length is, how much word limits matter, and what to do if you aren't sure how long a specific essay should be.

How Long Is a College Essay? First, Check the Word Limit

You might be used to turning in your writing assignments on a page-limit basis (for example, a 10-page paper). While some colleges provide page limits for their college essays, most use a word limit instead. This makes sure there's a standard length for all the essays that a college receives, regardless of formatting or font.

In the simplest terms, your college essay should be pretty close to, but not exceeding, the word limit in length. Think within 50 words as the lower bound, with the word limit as the upper bound. So for a 500-word limit essay, try to get somewhere between 450-500 words. If they give you a range, stay within that range.

College essay prompts usually provide the word limit right in the prompt or in the instructions.

For example, the University of Illinois says :

"You'll answer two to three prompts as part of your application. The questions you'll answer will depend on whether you're applying to a major or to our undeclared program , and if you've selected a second choice . Each response should be approximately 150 words."

As exemplified by the University of Illinois, the shortest word limits for college essays are usually around 150 words (less than half a single-spaced page). Rarely will you see a word limit higher than around 650 words (over one single-spaced page). College essays are usually pretty short: between 150 and 650 words. Admissions officers have to read a lot of them, after all!

Weigh your words carefully, because they are limited!

How Flexible Is the Word Limit?

But how flexible is the word limit? What if your poignant anecdote is just 10 words too long—or 100 too short?

Can I Go Over the Word Limit?

If you are attaching a document and you need one or two extra words, you can probably get away with exceeding the word limit by such a small amount. Some colleges will actually tell you that exceeding the word limit by 1-2 words is fine. However, I advise against exceeding the word limit unless it's explicitly allowed for a few reasons:

First, you might not be able to. If you have to copy-paste it into a text box, your essay might get cut off and you'll have to trim it down anyway.

If you exceed the word limit in a noticeable way, the admissions counselor may just stop reading your essay past that point. This is not good for you.

Following directions is actually a very important part of the college application process. You need to follow directions to get your letters of recommendation, upload your essays, send supplemental materials, get your test scores sent, and so on and so forth. So it's just a good general rule to follow whatever instructions you've been given by the institution. Better safe than sorry!

Can I Go Under the Word Limit?

If you can truly get your point across well beneath the word limit, it's probably fine. Brevity is not necessarily a bad thing in writing just so long as you are clear, cogent, and communicate what you want to.

However, most college essays have pretty tight word limits anyways. So if you're writing 300 words for an essay with a 500-word limit, ask yourself: is there anything more you could say to elaborate on or support your points? Consult with a parent, friend, or teacher on where you could elaborate with more detail or expand your points.

Also, if the college gives you a word range, you absolutely need to at least hit the bottom end of the range. So if you get a range from the institution, like 400-500 words, you need to write at least 400 words. If you write less, it will come across like you have nothing to say, which is not an impression you want to give.

What If There Is No Word Limit?

Some colleges don't give you a word limit for one or more of your essay prompts. This can be a little stressful, but the prompts generally fall into a few categories:

Writing Sample

Some colleges don't provide a hard-and-fast word limit because they want a writing sample from one of your classes. In this case, a word limit would be very limiting to you in terms of which assignments you could select from.

For an example of this kind of prompt, check out essay Option B at Amherst :

"Submit a graded paper from your junior or senior year that best represents your writing skills and analytical abilities. We are particularly interested in your ability to construct a tightly reasoned, persuasive argument that calls upon literary, sociological or historical evidence. You should NOT submit a laboratory report, journal entry, creative writing sample or in-class essay."

While there is usually no word limit per se, colleges sometimes provide a general page guideline for writing samples. In the FAQ for Option B , Amherst clarifies, "There is no hard-and-fast rule for official page limit. Typically, we anticipate a paper of 4-5 pages will provide adequate length to demonstrate your analytical abilities. Somewhat longer papers can also be submitted, but in most cases should not exceed 8-10 pages."

So even though there's no word limit, they'd like somewhere in the 4-10 pages range. High school students are not usually writing papers that are longer than 10 pages anyways, so that isn't very limiting.

Implicit Length Guideline

Sometimes, while there's no word (or even page) limit, there's still an implicit length guideline. What do I mean by this?

See, for example, this Western Washington University prompt :

“Describe one or more activities you have been involved in that have been particularly meaningful. What does your involvement say about the communities, identities or causes that are important to you?”

While there’s no page or word limit listed here, further down on page the ‘essay tips’ section explains that “ most essay responses are about 500 words, ” though “this is only a recommendation, not a firm limit.” This gives you an idea of what’s reasonable. A little longer or shorter than 500 words would be appropriate here. That’s what I mean by an “implicit” word limit—there is a reasonable length you could go to within the boundaries of the prompt.

But what's the proper coffee-to-paragraph ratio?

Treasure Hunt

There is also the classic "treasure hunt" prompt. No, it's not a prompt about a treasure hunt. It's a prompt where there are no length guidelines given, but if you hunt around on the rest of the website you can find length guidelines.

For example, the University of Chicago provides seven "Extended Essay" prompts . You must write an essay in response to one prompt of your choosing, but nowhere on the page is there any guidance about word count or page limit.

However, many colleges provide additional details about their expectations for application materials, including essays, on FAQ pages, which is true of the University of Chicago. On the school’s admissions Frequently Asked Questions page , they provide the following length guidelines for the supplemental essays: 

“We suggest that you note any word limits for Coalition or Common Application essays; however, there are no strict word limits on the UChicago Supplement essays. For the extended essay (where you choose one of several prompts), we suggest that you aim for around 650 words. While we won't, as a rule, stop reading after 650 words, we're only human and cannot promise that an overly wordy essay will hold our attention indefinitely. For the “Why UChicago?” essay, we suggest about 250-500 words. The ideas in your writing matter more than the exact number of words you use!”

So there you go! You want to be (loosely) in the realm of 650 for the extended essay, and 250-500 words for the “Why UChicago?” essay.

Help! There Really Is No Guidance on Length

If you really can't find any length guidelines anywhere on the admissions website and you're at a loss, I advise calling the admissions office. They may not be able to give you an exact number (in fact, they probably won't), but they will probably at least be able to tell you how long most of the essays they see are. (And keep you from writing a panicked, 20-page dissertation about your relationship with your dog).

In general, 500 words or so is pretty safe for a college essay. It's a fairly standard word limit length, in fact. (And if you're wondering, that's about a page and a half double-spaced.) 500 words is long enough to develop a basic idea while still getting a point across quickly—important when admissions counselors have thousands of essays to read!

"See? It says 500 words right there in tiny font!"

The Final Word: How Long Should a College Essay Be?

The best college essay length is usually pretty straightforward: you want to be right under or at the provided word limit. If you go substantially past the word limit, you risk having your essay cut off by an online application form or having the admissions officer just not finish it. And if you're too far under the word limit, you may not be elaborating enough.

What if there is no word limit? Then how long should a college essay be? In general, around 500 words is a pretty safe approximate word amount for a college essay—it's one of the most common word limits, after all!

Here's guidance for special cases and hunting down word limits:

If it's a writing sample of your graded academic work, the length either doesn't matter or there should be some loose page guidelines.

There also may be implicit length guidelines. For example, if a prompt says to write three paragraphs, you'll know that writing six sentences is definitely too short, and two single-spaced pages is definitely too long.

You might not be able to find length guidelines in the prompt, but you could still hunt them up elsewhere on the website. Try checking FAQs or googling your chosen school name with "admissions essay word limit."

If there really is no word limit, you can call the school to try to get some guidance.

With this advice, you can be sure you've got the right college essay length on lockdown!

Hey, writing about yourself can even be fun!

What's Next?

Need to ask a teacher or friend for help with your essay? See our do's and dont's to getting college essay advice .

If you're lacking in essay inspiration, see our guide to brainstorming college essay ideas . And here's our guide to starting out your essay perfectly!

Looking for college essay examples? See 11 places to find college essay examples and 145 essay examples with analysis !

Ellen has extensive education mentorship experience and is deeply committed to helping students succeed in all areas of life. She received a BA from Harvard in Folklore and Mythology and is currently pursuing graduate studies at Columbia University.

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Senior Thesis Formatting Guidelines

Contents and form.

Length : The required length is between 10,000 and 20,000 words, not counting notes, bibliography, and appendices. The precise length of the main body text must be indicated on the word count page  immediately following the title page . If a student expects the thesis to exceed 20,000 words, the student’s tutor should consult the Director of Studies. Please note that students’ requests to exceed 20,000 words must go through their tutors and that these requests must be made in early February. Any extension of the thesis beyond the maximum must be justified by the nature of the topic, or sustained excellence in the treatment of the subject, or both. Theses that receive permission to exceed 20,000 words can still be penalized if readers do not think that the excess length is warranted.

Acknowledgments : Please do not include acknowledgments in your final copy of the thesis. If you wish, you can add acknowledgments after your thesis has been read. Readers prefer not to know who directed your thesis, lest they be somehow swayed by that knowledge.

Illustrations : Illustrations, also called figures, might include anything from a photograph to a printed advertisement to a map to a chart. Illustrations may be inserted in the body of your thesis or included in an appendix at the end. Writers often choose to reference an illustration in the body of text, signaling to readers to refer to a particular figure that’s being discussed by turning to a nearby page or to an appendix (e.g., “See Figure 1.”) The inclusion of illustrations in a senior thesis, which has a fairly circumscribed audience, falls under fair use, so you do not need permissions to reproduce illustrations in your thesis. However, all images should be accompanied by a caption that identifies the image and may include brief explanatory text. You may also use the caption to attribute the source where you found the illustration (e.g., a url or the name of the archive where you photographed the item), or you can cite the illustration in a footnote or endnote. You do not need to cite your images in your bibliography. For more detailed guidelines on including illustrations in your thesis, see The Chicago Manual of Style or the MLA Style Manual .

Format : Pages should be 8 1/2" x 11". Margins should be 1 inch, and pages should be numbered. Do not right-justify. The lines of type must be double-spaced, except for quotations of five lines or more, which should be indented and single-spaced.

Style : If you have questions beyond those covered on this page, consult the University of Chicago's A Manual of Style or the Modern Language Association's Style Manual . Kate L. Turabian's A Manual for Writers is a good, inexpensive, brief guide to Chicago style. The Expository Writing Program guide, Writing with Sources , is very useful.

Table of Contents : Every thesis requires a Table of Contents to guide the reader.

Quotations : Quotations of four lines or fewer, surrounded by quotation marks, may be incorporated into the body of the text. Longer extracts should be indented and single-spaced; they should not be included in quotation marks. Each full quotation should be accompanied by a reference. Follow the general practice in the best periodicals in your field, and be consistent. Foreign words that are not quotations should be underlined or italicized.

Appendices : An appendix provides additional material that helps support your argument and is too lengthy to be included as a footnote or endnote. Appendices might include images, passages from primary texts in a non-English language or in your translation, or archival material that is difficult to access. It is rare but perfectly acceptable for theses to include appendices, so make sure to discuss with your tutor whether an appendix makes sense for your project.

Notes : You may use either footnotes (at bottom of page), endnotes (at end of the thesis) or MLA style parenthetical notes. However, for a History & Literature thesis, Chicago style is generally better. Footnote or endnotes are properly used:

• To state precisely the source or other authority for a statement in the text, or to acknowledge indebtedness for insights or arguments taken from other writers. Quotations should be given when necessary.
• To make minor qualifications, to prevent misunderstanding, or otherwise to clarify the text when such statements, if put in the text, would interrupt the flow.
• To carry further some topic discussed in the text, when such discussion is needed but does not fit into the text.

Bibliography : You must append a list of works cited to your thesis. It's a good idea to compile your bibliography as you write, rather than try to put it together all at once at the end (there are very powerful bibliography programs available, such as Zotero and Endnote, that generate bibliographies automatically). The purpose of the bibliography is to be a convenience to your reader. In the works cited list, primary and secondary sources should be listed under separate headings.

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Sample Title Page

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Thesis Format Template

How Long Should the Discussion Section Be? Data from 61,517 Examples

I analyzed a random sample of 61,517 full-text research papers, uploaded to PubMed Central between the years 2016 and 2021, in order to answer the questions:

What is the typical length of a discussion section? and which factors influence it?

I used the BioC API to download the data (see the References section below).

Here’s a summary of the key findings

1. The median discussion section was 1,115 words long (equivalent to 43 sentences, or 7 paragraphs), and 90% of the discussion sections were between 482 and 2,230 words.

2. Compared to other sections in a research paper, the discussion was about the same length as either the methods or the results, and double the length of the introduction .

3. The length of the discussion does not differ between review articles and original research articles .

4. The quality of the journal does not influence the length of the discussion section .

Overall length of the discussion section

Here’s a table that describes the length of a discussion section in terms of words, sentences, and paragraphs:

From these data, we can conclude that the discussion sections in most research papers are between 824 and 1,480 words long (32 to 57 sentences).

If you are interested, here are the links to the articles with the shortest and longest discussion sections.

The discussion section constitutes 29.5% of the total word count in a research article, equivalent to the length of either the methods or the results, and double the length of the introduction [source: How Long Should a Research Paper Be? ].

Length of the discussion for different article types

The following table shows the median word count of the discussion section for different study designs:

The data show no clear pattern since the discussions of review articles and original research articles have almost similar word counts. So we can conclude that there is no particular article type that requires a longer discussion section.

Length of the discussion in different journals

In order to study the influence of the journal quality on the length of the discussion section, I ran a Poisson regression that models the discussion word count given the journal impact factor. Here’s the model output:

The model shows that a higher journal impact factor is associated with a slightly longer discussion section. Although statistically significant, this effect is practically negligible since a 1 unit increase in the journal impact factor is associated with an increase of only 0.1% in the discussion word count. For the median article, this means that a 1 unit increase in the journal impact factor is associated with an approximate increase of 1 word in the discussion section.

• Comeau DC, Wei CH, Islamaj Doğan R, and Lu Z. PMC text mining subset in BioC: about 3 million full text articles and growing,  Bioinformatics , btz070, 2019.

Further reading

• How to Start a Discussion Section in Research? [with Examples]
• How Many References to Cite? Based on 96,685 Research Papers
• How Old Should References Be? Based on 3,823,919 Examples

• How Long Should a Thesis Be
• How Long Should a Thesis Be? Tips for Creating a Perfect Paper

Thesis Outline Part 1 – Abstract, Contents, and Introduction

Thesis outline part 2 – methods, results, discussion, thesis outline part 3 – conclusions, recommendations, and references.

In academic writing, a thesis is related to complex papers. Usually, it is called a Master’s or a Doctoral thesis and can be compared to a dissertation. The main differences between them are size and width of uncovered topic. How long should a thesis be? 

Undeniably, it takes months to complete a well-researched work and it's easier to delegate this difficult task to professionals who will help write a thesis quickly and with quality in mind.

• Students place abstract on 2 pages
• An introduction should be placed on 3-5 pages
• The Methods section can be up to 10 pages long
• Results take 10 pages
• Discussion can be placed on 15 pages
• The conclusion takes 2-3 pages
• Appendix and other auxiliary parts of work can take up to 30 pages
• Complete paper contains 60-70 pages

If we take the article length, a dissertation should be at least three articles long. Read our guide to identify how long is a dissertation . Thesis takes space of one article. When university students choose a thesis to work on instead of a bibliographic essay, they do it for leaving a possibility to evaluate a research in the future.

There are more questions related to thesis writing appearing. What to include into a good text? If people make theses longer, will they become better? This article is a universal answer to all specific questions concerning proper writing.

Every academic paper begins with title page. Its structure depends on the chosen formatting style. An abstract follows it. This is an important part that describes thesis utility. It must be short and take 1-2 paragraphs, about 400 words and contain short summary of results, methods, etc. Here are questions to answer in this part:

• What was the reason to write this paper?
• What thesis statement to prove or disprove?
• What were your instruments? (describe main methods of research)
• What did you find out?
• Why are the results important?

Avoid citations, try to use more numbers. An abstract for dissertation or thesis should be qualitative. After it, the table of contents follows. Group all headings and subheadings into one complex list. If figures and tables are used, enlist their names, point page number of each one.

The first big part is the introduction for thesis . It may seem similar to an abstract. It pursues different goals – reader hooking, providing background information and logical transition to your own research. Here is what you need to disclose in this chapter:

• Enough background information about previous researches should be presented to make readers understand place of text in science system.
• Give an explanation concerning contents – what will be included into thesis.
• Provide readers with verbal ‘road maps’.
• Cite previous works. The citations must be related to text’s goals. Do not list everything you have read about subject.

These sections must take three pages of paper, excluding contents and table lists.

These are essential parts. They contain information concerning your own research. Answering main question of our post (how long should a thesis be?), these parts must take at least 30-40 pages. Let’s find out what Ph.D or Master’s thesis paper shoud present in these chapters.

The methods section is text’s explanatory part. There you have to provide readers with clear information and details that allow repeating the research and experiments. Traditionally, methods section is divided into three parts – materials, participants, ways of analysis. Materials imply full description of all instruments and quntitative and qualitative methods used for making research.

Participants part, just like a research paper discussion , describes people or subjects analyzed, including regulations of choice. Ways of analysis present all research approaches used to get results. This part describes area and circumstances of your experiments and helps to identify if they were legitimate and relevant.

Results part contains relevant statements of observations with statistical data, graphs, tables, etc. The section is divided into paragraphs, where key results are arranged into sentences at beginning. Do not forget about negative results, if possible. The main goal of section is data structuring to be helpful for readers to make own conclusions. Mention the nature of data found.

Discussion part is where you interpret results and adjust them to a thesis statement and goals. Disclose patterns and relationships between the observations found, find possible exceptions and discuss if the results correlate with previous researches. Each interpretation you make should be supplied with sufficient evidence. Define if materials are working for the future researches as well. This chapter is the richest in referencing to background material and other parts of your paper.

Here you make the strongest statement concerning observations. Highlight the information you want readers to remember. Explain how the results correlate with the problems you have indicated in the introduction. Describe all new things that are significant in finding a solution and provide limitations examples .

The recommendations part is for giving advice and indicating other actions that will help to solve particular problems. Sound your own opinion about the direction of future research. Most of the time you have to write it. Just like a research proposal . 

Acknowledgment for thesis  is a paragraph where you mention everyone who helped you with composition. Place all cited and used information resources into one list or form an annotated bibliography if needed.

All kinds of data used in writing, not cited and used resources directly go to the appendices part. This section is last. Along with conclusions they may take up to 10 pages.

What is the direct answer to our question? How long should a thesis be? Experts from a writing site assume, it takes about 60-70 pages. It depends on your research and subject. The length does not matter, actually. The most important thing you need to do is make a complete and complex paper. Provide everything from A to Z - no one will recall the thesis length.

Have you started doing a Ph.D. yet? And now you wonder what it takes to write a dissertation. How long is it supposed to be? How much time will you need to complete it? What is the best way to approach a dissertation? Let us try to answer the most common questions associated with academic research o...

College puts every student through an obstacle course. Whether labs or essays or researches, every type of assignment requires scrupulous work. It means a student is expected to be switched on all the time. Is it possible to meet all the requirements? A better question is, do you need it? From study...

Writing a master’s thesis requires a lot of patience. It's not something you can create in a few days. It’s a large scale project, so you’ll have to make a strict schedule and write a little piece every day. Do you feel it's a difficult job for you and you need thesis help? Instead of devoting your ...

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• Dissertation

How to Write a Thesis or Dissertation Introduction

Published on September 7, 2022 by Tegan George and Shona McCombes. Revised on November 21, 2023.

The introduction is the first section of your thesis or dissertation , appearing right after the table of contents . Your introduction draws your reader in, setting the stage for your research with a clear focus, purpose, and direction on a relevant topic .

Your introduction should include:

• Your topic, in context: what does your reader need to know to understand your thesis dissertation?
• Your focus and scope: what specific aspect of the topic will you address?
• The relevance of your research: how does your work fit into existing studies on your topic?
• Your questions and objectives: what does your research aim to find out, and how?
• An overview of your structure: what does each section contribute to the overall aim?

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Table of contents

How to start your introduction, topic and context, focus and scope, relevance and importance, questions and objectives, overview of the structure, thesis introduction example, introduction checklist, other interesting articles, frequently asked questions about introductions.

Although your introduction kicks off your dissertation, it doesn’t have to be the first thing you write — in fact, it’s often one of the very last parts to be completed (just before your abstract ).

It’s a good idea to write a rough draft of your introduction as you begin your research, to help guide you. If you wrote a research proposal , consider using this as a template, as it contains many of the same elements. However, be sure to revise your introduction throughout the writing process, making sure it matches the content of your ensuing sections.

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Begin by introducing your dissertation topic and giving any necessary background information. It’s important to contextualize your research and generate interest. Aim to show why your topic is timely or important. You may want to mention a relevant news item, academic debate, or practical problem.

After a brief introduction to your general area of interest, narrow your focus and define the scope of your research.

You can narrow this down in many ways, such as by:

• Geographical area
• Time period
• Demographics or communities
• Themes or aspects of the topic

It’s essential to share your motivation for doing this research, as well as how it relates to existing work on your topic. Further, you should also mention what new insights you expect it will contribute.

Start by giving a brief overview of the current state of research. You should definitely cite the most relevant literature, but remember that you will conduct a more in-depth survey of relevant sources in the literature review section, so there’s no need to go too in-depth in the introduction.

Depending on your field, the importance of your research might focus on its practical application (e.g., in policy or management) or on advancing scholarly understanding of the topic (e.g., by developing theories or adding new empirical data). In many cases, it will do both.

Ultimately, your introduction should explain how your thesis or dissertation:

• Helps solve a practical or theoretical problem
• Addresses a gap in the literature
• Builds on existing research
• Proposes a new understanding of your topic

Perhaps the most important part of your introduction is your questions and objectives, as it sets up the expectations for the rest of your thesis or dissertation. How you formulate your research questions and research objectives will depend on your discipline, topic, and focus, but you should always clearly state the central aim of your research.

If your research aims to test hypotheses , you can formulate them here. Your introduction is also a good place for a conceptual framework that suggests relationships between variables .

• Conduct surveys to collect data on students’ levels of knowledge, understanding, and positive/negative perceptions of government policy.
• Determine whether attitudes to climate policy are associated with variables such as age, gender, region, and social class.
• Conduct interviews to gain qualitative insights into students’ perspectives and actions in relation to climate policy.

To help guide your reader, end your introduction with an outline  of the structure of the thesis or dissertation to follow. Share a brief summary of each chapter, clearly showing how each contributes to your central aims. However, be careful to keep this overview concise: 1-2 sentences should be enough.

I. Introduction

Human language consists of a set of vowels and consonants which are combined to form words. During the speech production process, thoughts are converted into spoken utterances to convey a message. The appropriate words and their meanings are selected in the mental lexicon (Dell & Burger, 1997). This pre-verbal message is then grammatically coded, during which a syntactic representation of the utterance is built.

Speech, language, and voice disorders affect the vocal cords, nerves, muscles, and brain structures, which result in a distorted language reception or speech production (Sataloff & Hawkshaw, 2014). The symptoms vary from adding superfluous words and taking pauses to hoarseness of the voice, depending on the type of disorder (Dodd, 2005). However, distortions of the speech may also occur as a result of a disease that seems unrelated to speech, such as multiple sclerosis or chronic obstructive pulmonary disease.

This study aims to determine which acoustic parameters are suitable for the automatic detection of exacerbations in patients suffering from chronic obstructive pulmonary disease (COPD) by investigating which aspects of speech differ between COPD patients and healthy speakers and which aspects differ between COPD patients in exacerbation and stable COPD patients.

Checklist: Introduction

I have introduced my research topic in an engaging way.

I have provided necessary context to help the reader understand my topic.

I have clearly specified the focus of my research.

I have shown the relevance and importance of the dissertation topic .

I have clearly stated the problem or question that my research addresses.

I have outlined the specific objectives of the research .

I have provided an overview of the dissertation’s structure .

You've written a strong introduction for your thesis or dissertation. Use the other checklists to continue improving your dissertation.

If you want to know more about AI for academic writing, AI tools, or research bias, make sure to check out some of our other articles with explanations and examples or go directly to our tools!

Research bias

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The introduction of a research paper includes several key elements:

• A hook to catch the reader’s interest
• Relevant background on the topic
• Details of your research problem

and your problem statement

• A thesis statement or research question
• Sometimes an overview of the paper

Don’t feel that you have to write the introduction first. The introduction is often one of the last parts of the research paper you’ll write, along with the conclusion.

This is because it can be easier to introduce your paper once you’ve already written the body ; you may not have the clearest idea of your arguments until you’ve written them, and things can change during the writing process .

Research objectives describe what you intend your research project to accomplish.

They summarize the approach and purpose of the project and help to focus your research.

Your objectives should appear in the introduction of your research paper , at the end of your problem statement .

Scope of research is determined at the beginning of your research process , prior to the data collection stage. Sometimes called “scope of study,” your scope delineates what will and will not be covered in your project. It helps you focus your work and your time, ensuring that you’ll be able to achieve your goals and outcomes.

Defining a scope can be very useful in any research project, from a research proposal to a thesis or dissertation . A scope is needed for all types of research: quantitative , qualitative , and mixed methods .

To define your scope of research, consider the following:

• Budget constraints or any specifics of grant funding
• Your proposed timeline and duration
• Specifics about your population of study, your proposed sample size , and the research methodology you’ll pursue
• Any inclusion and exclusion criteria
• Any anticipated control , extraneous , or confounding variables that could bias your research if not accounted for properly.

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When will cicadas go away? Depends where you live, but some have already started to die off

After weeks of hearing the near-constant noise from the periodical cicadas that have emerged in nearly 20 states this year, you may soon be hearing a lot more silence.

After spending 13 or 17 years underground and weeks above ground, some of the earliest periodical cicadas are completing their life cycle and starting to die off. The cicadas, the 13-year Brood XIX in the Southeast and the 17-year Brood XIII in the Midwest, are part of a rare occurrence − the two broods have not emerged together since 1803.

If you're in one of the roughly 17 states that has seen either brood (or both, if you live in Illinois or Iowa), the cicadas' time to eat, mate, lay eggs and die may be starting to come to a close.

Here's what to expect about when Brood XIX and Brood XIII cicadas will start to die off.

'One in a million': 2 blue-eyed cicadas spotted in Illinois as 2 broods swarm the state

When will Brood XIX, Brood XIII cicadas start to die off?

The Brood XIX cicadas that emerged in mid-April are already declining, said Gene Kritsky, a cicada expert and professor in the Department of Biology at Mount St. Joseph University in Cincinnati, Ohio.

Kritsky previously told USA TODAY the first adult cicadas were reported to Cicada Safari, a cicada tracking app developed by Mount St. Joseph University, on April 14 in Georgia, parts of Tennessee and Alabama. In the following week, they came out in North Carolina and South Carolina.

Brood XIII cicadas in central Illinois will see declines in about three weeks, Kritsky said, and in about four weeks in Chicago.

How long will the cicadas be above ground?

How long cicadas live depends on their brood and if they are an annual or periodical species.

The two periodical broods this summer are Brood XIX, which have a 13-year life cycle, and Brood XIII, which have a 17-year life cycle.

Once male and female periodical cicadas have mated and the latter has laid its eggs, the insects will die after spending only a few weeks above ground − anywhere from three to six weeks after first emerging.

That means many of this year's periodical cicadas are set to die in June, though some may have already died off in late May and others could last until early July, depending on when they emerged.

The nymphs of annual cicadas remain underground for  two to five years , according to the Missouri Department of Conservation. These cicadas are called " annual " because some members of the species emerge as adults each year.

What is the life cycle of a cicada?

The  life cycle of a cicada  starts with mating. The female then lays eggs in holes made in tree branches and shrubs,  National Geographic reports . The eggs will hatch after six to 10 weeks and the cicada nymphs will burrow themselves into the ground, attaching to the tree's roots.

The cicadas will remain underground for a " dormant period " of two to 17 years, depending on the species. Then they emerge in adult form, according to National Geographic.

2024 cicada map: Where to find Broods XIII, XIX this year

The two cicada broods were projected to emerge in a combined 17 states across the South and Midwest. They emerge once the soil eight inches underground reaches 64 degrees, which began in many states in April and May and will last through late June.

The two broods  last emerged together in 1803 , when Thomas Jefferson was president.

Judge orders Steve Bannon to report to prison on July 1 for contempt of Congress sentence

WASHINGTON — A federal judge on Thursday ordered former Trump adviser Steve Bannon to report to prison on July 1 to begin a four-month prison sentence for defying subpoenas from the Jan. 6 Committee after a higher court rejected his appeal.

Bannon was found guilty on two counts of contempt of Congress in July 2022 for defying the committee’s subpoenas, but his sentence had been put on hold while he appealed the case. U.S. District Judge Carl Nichols said Thursday he did not believe that the “original basis” for his stay of the imposition of Bannon's sentence existed any longer after an appeals court upheld Bannon's conviction. Bannon could still appeal Nichol’s ruling that he must report to prison.

Bannon was sentenced more than a year and a half ago, in October 2022, to four months behind bars, the same sentence currently being served by former Trump adviser Peter Navarro , who also refused to comply with a Jan. 6 Committee subpoena.

“The defendant chose allegiance to Donald Trump over compliance with the law," Assistant U.S. Attorney Molly Gaston, who now serves on special counsel Jack Smith's team, told jurors during closing arguments in 2022.

Bannon's sentence was put on hold pending appeal, and his lawyers made their case to a three-judge federal appeals court panel in November. The appeals court upheld Bannon's conviction in May , and federal prosecutors soon filed a motion asking Nichols to order Bannon to report to prison. Federal prosecutors told Nichols there was "no legal basis" for the continued stay of the sentence after the federal appeals court rejected the appeal.

Bannon’s lawyers argued that the sentence should be stayed until they appeal it to the full appeals court and the Supreme Court. Any delay, of course, would benefit Bannon if Trump is elected president in November and decides — just as he did on the last day of his presidency on Jan. 20, 2021 — to pardon Bannon on federal criminal charges.

In a post on his Truth Social website, Trump said the sentence is a “Total and Complete American Tragedy" and suggested that the members of the Jan. 6 committee be prosecuted instead.

Bannon is set to  go to trial  on separate state charges in New York later this year in a case involving allegations he  defrauded donors who gave money to build a wall  on the southern U.S. border. He's pleaded not guilty. Bannon had been charged in the same alleged scheme by federal prosecutors before Trump pardoned him just two weeks after the Capitol attack.

Bannon smiled as he went through security to enter the courthouse Thursday morning. A person nearby said “Trump ‘24!” to him and Bannon smiled and shook his hand.

Following the judge’s decision, he looked calm and stayed smiling. Bannon's lawyer, David Schoen, sprung into action, becoming much more passionate than he’d been during the rest of the hearing. 

Judge Nichols told him: “One thing you have to learn as a lawyer is that when the judge has made his decision, you don’t stand up and start yelling,” adding through Schoen’s protests: “I’ve had enough.”

“I’m not yelling,” Schoen retorted, saying he was “passionate.”

“You’re sending a man to prison who thought he was complying with the law, we don’t do that in my system,” Schoen said, calling the decision “contrary to our system of justice.”

“I think you should sit down,” Nichols responded. 

Nichols, a Trump appointee, has overseen a number of Jan. 6 cases. He's the judge who rejected the government's use of an obstruction of an official proceeding charge, which has been used against hundreds of Jan. 6 defendants, as well as Trump himself. That case ultimately bubbled up to the Supreme Court, which heard oral arguments on the use of the statute in April . On Wednesday, Nichols sentenced a Jan. 6 defendant who assaulted law enforcement officers with bear spray — and who was caught thanks to a sting operation that a woman launched on the dating app Bumble — to more than six years in federal prison.

Ryan J. Reilly is a justice reporter for NBC News.

Victoria Ebner is a researcher with NBC News based in Washington, D.C. 

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Honors student produces prize-winning research on loneliness

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In her honors thesis, recent graduate Amber Duffy describes how loneliness influences a person’s ability to respond to stress

Amber Duffy, who graduated last semester magna cum laude , didn’t always plan to write an honor’s thesis.

She came to the University of Colorado Boulder on a pre-med track, studying neuroscience, but an introductory psychology class knocked her off that path and inspired her to change her major.  

“I really liked the behavioral aspect of psychology,” she says.

She liked psychology so much, in fact, that she wasn’t content simply to study it. She wanted to contribute to it. “If I’m not going to do medical school anymore,” she remembers thinking, “I should delve into research.”

Recent psychology and neuroscience graduate Amber Duffy won the the Outstanding Poster Presentation Talk award at the Society for Personality and Social Psychology’s Annual Convention in San Diego, recognizing her research on loneliness.

She contacted Erik Knight , a CU Boulder assistant professor of psychology and neuroscience, with whom she’d taken a class her sophomore year, and he invited her to join his lab . She ended up working there for two years, during which time she decided to write an honor’s thesis.

The topic? Loneliness and its effect on young adults’ stress responses.

Why loneliness?  

Duffy’s interest in loneliness isn’t purely academic. Many of her friends and family have struggled with it for years, even before the pandemic, she says. And she herself, the daughter of a Taiwanese mother and a Pennsylvanian father, has often felt its sting.  

“Growing up in a multicultural family in my predominantly white town”—Castle Rock, Colorado—“it was hard for me to connect with people sometimes,” she says. “I would learn about my mom’s culture at home and then go to school or talk with friends, and they just didn’t understand how I lived.”

Her concerns over loneliness only increased when she learned of Surgeon General Dr. Vivek H. Murthy’s warning that the United States is suffering from a loneliness epidemic.

“The mortality impact of being socially disconnected is similar to that caused by smoking up to 15 cigarettes a day,” Murthy states.  

Hearing this spurred Duffy to action. She wanted to contribute to the fight against loneliness and its potentially negative consequences.

“If we expand our knowledge of loneliness,” she says, “maybe there’s a way we can come up with a more substantial treatment.”

More gas, less brakes

For her honors experiment, Duffy gathered 51 CU Boulder undergraduates between the ages of 18 and 34 and divided them randomly into a control condition and an experimental condition. Those in the former provided a low-stress comparison to those in the latter, who were put through the wringer.

First, the subjects in the experimental condition had to interview for a high-stakes job Duffy and Knight had concocted specifically for the study.

“We told them, in the moment, ‘You have five minutes to prepare a five-minute speech on why you’re the perfect applicant,’” says Duffy.

Immediately following that, subjects had to solve subtraction problems for five minutes, out loud, perfectly, starting at 6,233 and going down from there in increments of 13. “If they made a mistake,” says Duffy, “they had to start over.”

While the subjects ran these gauntlets, Duffy monitored their heart-rate variability (HRV), or the change in interval between heartbeats, and their pre-ejection period (PEP), or the time it takes for a heart to prepare to push blood to the rest of the body. Both serve as indicators of how a person’s stress-response system is functioning, Duffy explains. 

Finally, when the stress tests were done, the subjects completed the UCLA Loneliness Scale Version 3 questionnaire, which research has found to be a reliable means of measuring loneliness.

Duffy had hypothesized that lonelier subjects would have more pronounced stress responses than less lonely subjects, and indeed that’s what her data revealed.

Lonelier subjects had higher heartrates, stronger responses from their sympathetic nervous systems (SNS) and weaker responses from their parasympathetic nervous systems (PNS). Duffy likens the SNS, which controls the fight-or-flight response, to a car’s gas pedal and the PNS, which counterbalances the SNS, to a car’s brakes.

When met with stressful situations, then, lonelier individuals had more gas and less brakes, which Duffy says could have long-term health implications.

Yet she is also quick to point out that more research needs to be done, preferably with more subjects.

If we expand our knowledge of loneliness, maybe there’s a way we can come up with a more substantial treatment.”

“We only had 51 people. An increase in sample size would help with more reliable data,” she says. “It’s also important to look at more clinical and diverse populations because there are other factors that could affect loneliness levels.” 

Posters, prizes and professorships

Duffy submitted an abstract of her research to The Society for Personality and Social Psychology’s Annual Convention in San Diego, where she hoped to present a poster, thinking this would be a nice, low-key way of getting some conference experience under her belt.

Her abstract was accepted. But then a conference organizer asked her if, in addition to presenting a poster, she could also give a fifteen-minute talk. She would be the only undergraduate at the conference to do so.

Duffy balked. The thought of speaking to a roomful of PhDs intimidated her. “Most of my life I’ve heard how cutthroat academia is,” she says. But she ultimately agreed, and she was glad she did.

Her talk and poster presentation went so well that not only did she receive interest and encouragement from several doctoral programs, but she also won an award that she didn’t even know existed: the Outstanding Poster Presentation Talk award.

“In the middle of my poster presentation, a woman came up to me—I didn’t know who she was—and said, ‘I have a check here for you for $500.’ I didn’t know that was supposed to happen, but it was great!”

Now graduated, Duffy isn’t 100% sure what her next steps will be, but she’s leaning toward one day pursuing a PhD. 

“When you get a PhD, you get to do research and also work with students,” she says. “I think it would be fun to be a professor and give back in that way.”

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BBC Verify is becoming a tool for elite control of discourse

There’s a fine line between clarification and debate. Too often fact-checks stray into the latter

If you spend any time with members of our new establishment – academics, quangocrats, the BBC – and especially if you conceal your identity as a Telegraph reader so they speak freely, you will learn something rather strange. They are obsessed with misinformation and disinformation .

I assure you, people like this genuinely believe that in the new social media world the ill-informed populace is easy prey to false beliefs, conspiracies, and malign state interference. They believe that you are too stupid to make your own mind up about things or distinguish between the true and the false. And they think it’s the government’s job – or perhaps theirs – to do it for you instead.

One obvious problem with this thesis is that in recent years an awful lot of misinformation has come from governments themselves: Trump’s supposed collusion with Russia, the view that an economic crash was inevitable if we voted to leave the EU, the refusal to countenance the lab leak theory about Covid, and the reluctance for a long time, in the teeth of obvious evidence, to drop the belief that the Covid vaccine stopped transmission of the virus.

Perhaps sensing this, the authorities have smiled instead on the growth of so-called “fact checking” outfits, the best known of which is BBC Verify, ubiquitous on the BBC nowadays. Their self-regarding takes on the news may seem merely comic, but they are actually dangerous, and especially so during an election campaign – for in trying to convey an authoritative view they are more often, as Orwell once put it, giving “an appearance of solidity to pure wind”.

Take Friday night’s 7-sided “leader” debate , fact checked live by BBC Verify’s Ben Chu. What’s wrong with that, you might ask?

The problem is that they aren’t checking facts; they are also checking opinion. They can’t be experts in everything, so they have to go to other sources of authority, other supposed experts. But these people are often not neutral either. BBC Verify fact-checked Nigel Farage’s views on net zero on Friday by reference to the views of the Climate Change Committee. But anyone who knows anything about net zero knows that, while the Committee’s views may be received wisdom amongst much of the establishment, they are definitely controversial. They have to be open to debate. You can’t say that Farage’s views are just comment but the Committee’s views are fact.

Similarly, a month back Ben Chu looked on X at the UK’s post-Brexit trade performance, pointing to the OBR’s estimate of a 15 per cent fall in trade to make his argument. But that estimate is itself based on other estimates, now dated, and themselves questionable. It isn’t a fact: it’s a view, and one that can and must be debated.

This matters because very often in politics the facts only take you so far: it is the interpretation that counts. It’s a fact that net immigration to the UK in 2023 was 685,000 people. Is that good or bad? It depends whether you think it contributes to economic growth or not (which is controversial); on how you value social cohesion against the economy; and on how you value moral obligations such as taking in refugees. None of this is objective fact. It’s all open to interpretation and debate. That’s what an election is about.

That’s why the whole BBC Verify programme is based on a fallacy. On most political issues not only is there simply no authoritative interpretation of the facts, but what a fact tells you depends on the interpretation you bring to it. The only way to reach an outcome is to have free debate, allow all to make their case, and see who wins the argument.

So BBC Verify should confine itself to clarifying the issues, and then let people make their own mind up. But surely that is what the BBC should be doing anyway. So why do we need BBC Verify at all? Maybe we don’t. 

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Stocks for the Long Run? Setting the Record Straight

Editor’s Note: This is the final article in a three-part series that challenges the conventional wisdom that stocks always outperform bonds over the long term and that a negative correlation between bonds and stocks leads to effective diversification. In it, Edward McQuarrie draws from his research analyzing US stock and bond records dating back to 1792.

CFA Institute Research and Policy Center recently hosted a panel discussion comprising McQuarrie ,  Rob Arnott ,  Elroy Dimson ,  Roger Ibbotson , and  Jeremy Siegel .  Laurence B. Siegel  moderated and Marg Franklin, CFA , president and CEO of CFA Institute introduced the debate .

Edward McQuarrie:

In my first two blog posts, I reviewed the new historical findings presented in my Financial Analysts Journal paper . Relative to when Jeremy Siegel first formulated the Stocks for the Long Run thesis 30 years ago, better and more complete information on 19 th century US stock and bond returns has emerged. Likewise, courtesy of the work of Dimson and others, a far richer and more complete understanding of international returns is now in hand.

I summarized the new historical findings in my paper’s title: “Stocks for the Long Run? Sometimes Yes, Sometimes No.”

In this concluding post, I will highlight the implications of these new findings for investors today. I will address several misconceptions that I’ve encountered interacting with readers of the paper.

Misconception #1: McQuarrie doubts whether stocks are a good investment over the long term.

Nope. Rather, I want you to adjust your expectations for the long-term wealth accumulation that you can expect from holding stocks, especially a 100% stock portfolio, over your idiosyncratic personal time horizon.

Here’s why I think some adjustment of expectations is necessary.

Let me first acknowledge that no author is responsible for what readers do with their work once published and diffused, so what follows is not a criticism of Siegel or his research.

That said, some readers of Siegel’s Stocks for the Long Run conclude: “If I can hold for decades, stocks are a sure thing, a no-lose proposition. It could be a wild ride over the short-term, but not over the long-term, where buying and holding a broad stock index essentially guarantees a strong return.”

Siegel never said any such thing. But I can assure you, more than a few investors drew the conclusion that for holding periods of 20 years or more, stocks are like certificates of deposits with above-market interest rates.

The inference that my paper attempts to refute is that stocks somehow cease to be a risky investment once they are held for decades. I presented numerous cases where investors in other nations had lost money in stocks over holding periods of 20 years or more. And to make the demonstration more compelling, I first excluded war-torn nations and periods.

My point is: Stocks are NOT guaranteed to make you money over the long term.

In fact, stocks have often rewarded investors over the long term, despite large fluctuations in the short term. Patient investors have reaped huge rewards, especially US investors fortunate enough to be active during the “American Century.”

• Over the 20 years from the end of 1948 to the end of 1968, an investment in US stocks would have turned $10,000 into almost $170,000.
• Over the 18 years from the end of 1981, that investment would have turned $10,000 into almost $175,000
• And over the 36 years from 1922 to 1958, that investment would have turned $10,000 into almost $340,000, despite the, ahem, hiccup that occurred after 1929.

Huge rewards can be reaped from stocks. But there is no guarantee of any reward.

You make a wager when you invest in stocks. It remains a wager when you invest in a broadly diversified index such as the S&P 500. And it is still a bet even when you hold it for 20 years.

Odds are good that your bet will pay, especially if you are investing in a globally dominant nation, such as the US in the 20 th century, or the UK in the 19 th century.

But the odds never approach 100%.

Misconception #2: McQuarrie wants me to own more bonds.

It would be more correct to say that I wish to rehabilitate bonds from the disrepute in which they fell after their terrible, horrible, no good, very bad performance in the decades from 1946 to 1981. Those years dominated the record in the Stocks, Bonds, Bills & Inflation yearbook compiled by Roger Ibbotson and colleagues when Siegel first formulated his thesis.

The new historical record reveals that the divergent performance of stocks and bonds from 1946 to1981 was unique. Nothing like it had ever occurred in the century-and-a-half before. The most recent four decades look quite different, with stock and bond performance again approximating parity.

Here is where it becomes important to tread very carefully in constructing a forward-looking interpretation of the historical record with respect to the equity premium, i.e., the advantage of owning stocks instead of bonds.

If you calculate the mean or average stock performance relative to bond performance over the entire two-century US record, you get an equity premium of about 300 to 400 bp annualized. That’s huge. Compound that for 20 or 30 years and you’ll find yourself chanting “Stocks for the Long Run.”

Outcomes by Century

Note. Reproduced from “Stocks for the Long Run? Sometimes Yes, Sometimes No.” Arithmetic mean of real total returns. Wealth is the value of $1.00 invested for 100 years (compounded returns can be extracted by taking the 100 th root). Equity premium is the mean of the annual subtractions. Standard deviations are in parentheses. Means with superscript a are different across periods and those with superscript b are different within period (t-tests with heterogenous variance, all p-values < .01).

If you separate out the 19 th century from the 20 th century, as I did in the table, you find: The equity premium for the 19 th century was just under zero, while the equity premium for the 20 th century was just over 600 bp.

Average those two together, along with the omitted years from the 18 th and 21 st centuries to get a complete record, and you get the expected result: an historical equity premium of 300+ bp, in the new historical record, which is consistent with the old record.

But can you be confident that stocks will outperform bonds by 300 bp per year over your decade or two or three, over your personal horizon?

Of course not. The equity premium has exhibited too much variance even over very long intervals.

Let’s return to Misconception #2 and drill down. In the old historical record, first compiled by Ibbotson back to 1926 and then extended by Siegel back to 1802, a long-term investor had no good reason to own any bonds. At all.

In the old record, stocks always outperformed bonds, and the outperformance became increasingly dependable and grew larger in magnitude as the holding period stretched out to 20 years, 30 years, and longer.

The only justification for holding any bonds was if the investor lacked the stomach for the short-term volatility of stocks. Bonds were for the pusillanimous investor who didn’t have the spine to harvest the magnificent long-term returns on stocks.

Spineless investors had to settle for the much lower returns offered by a bond allocation because of their urgent need to dampen the intolerable short-term volatility of stocks.

Any financial adviser will confirm that many clients can’t abide the short-term volatility of a 100% stock portfolio. One of several contributions of Siegel’s work was to stiffen the spines of investors who were prey to such fears but who could be persuaded by evidence.

Such risk-averse investors could only maximize utility, net of return and risk, by including bonds in their portfolios, sacrificing return to reduce risk to a tolerable level.

Using the Ibbotson-Siegel historical data, the investor with a cast iron stomach would be inclined to invest 100% of their long-term funds in stocks. Given their high tolerance for risk, it would be irrational to do otherwise.

On the new historical record, in which stocks do not always beat bonds, the choice is less clear. A balanced portfolio, such as the 60/40 portfolio popularized by Peter Bernstein , might not produce any less return than a 100% stock portfolio. It might even produce somewhat more wealth if stocks go through a bad stretch.

Conversely, a 60/40 portfolio will almost certainly be less volatile than a 100% stock portfolio for reasons explained by the late Harry Markowitz : the expected lack of correlation between stocks and bonds and bonds’ historically lower volatility.

In the absence of certainty that stocks will outperform bonds, combined with the near certainty that a balanced portfolio of stocks and bonds will be less volatile than a 100% stock portfolio and subject to more shallow drawdowns, a balanced portfolio becomes a viable option for any investor.

That’s the gist of the new historical record.

Misconception #3: McQuarrie steers US investors away from owning international stocks .

This one surprised me when I first heard it. I never dreamed that the tables in my preceding post would be interpreted that way.

In my paper, I tabulated bad periods for stocks — periods showing equity deficits where stocks underperformed bonds — across 19 nations outside of the US. I showed multiple instances of losses on stocks over 20 years, 30 years, and more rarely, 50 years.

But that doesn’t mean that international stocks are a bad bet for US investors going forward. I would expect that sometimes international stocks will outperform US stocks and sometimes US stocks will outperform. It varies by regime and can’t be predicted any more than the future performance of US stocks can be known in advance.

How then to interpret the woeful episodes of underperformance by international stocks tabulated in the paper?

First, each of those international results was cherry-picked. I had a 300-year record of UK stock performance available, courtesy of Bryan Taylor at Global Financial Data. That means I had 281 twenty-year rolls to choose from: 1700 to 1719, 1701 to 1720, etc.

I picked the very worst one for the UK entry in the 20-year column in my table. For the other 18 countries, I typically had between 150 and 200 years from which to cherry-pick the very worst episode.

The purpose of the exercise was to expand the sample size of stock market histories beyond a one-market, one-century record: the period from 1926 in the United States, which has dominated most investors’ historical understanding ever since Ibbotson first assembled the Stocks, Bonds, Bills & Inflation record in 1976.

In that one-market, one-century record, stocks always do well if you hold on long enough, and stocks always beat bonds over those long periods.

But that result was obtained in one market over one century. The 19 th century US data I compiled gave me a second century, but still only for that one market.

Paul Samuelson among others famously observed that “history has a sample size of one.” That’s true if you confine attention to one national history and one century. When the only historical record available covers but one nation, and only during the period when it rose to world dominance with the largest economy — the United States post-1926 — generalization is fraught indeed.

Would stock investors fare just as well in a nation less favorably situated, over a less sunny period? There was no way to know, decades ago, when Siegel first assembled the Stocks for the Long Run thesis. The international record was very sparse back then.

In my thinking, the newly emerged international record, launched initially by William Goetzmann and Philippe Jorion in 1999, takes the historical record from a sample size of one to a sample of about 40 (20 nations across two centuries). Or, if you will, from 100 market years to 4,000 market years.

As a rule, expanding the sample size helps to refine the estimate of the range of potential outcomes. If you walk down Fifth Avenue in Manhattan with a surveyor’s laser sight and measure the height of the first 100 adults you pass, you will likely infer that most US adults are between five and six feet tall. You might find a few individuals shorter than five feet, and you will probably find a few taller than six feet.

If it is a reasonably co-ed sample, you might formulate the hypothesis that US males are taller than females on average, but you wouldn’t have much confidence in that generalization if the sample consisted of only 23 women and 77 men.

To continue the metaphor, suppose you added to the sample by walking down the main street of Stockholm. Your estimate of the maximum adult height to be found in a sample of 100 people would probably increase.

Switching up the metaphor, suppose the first sample of 100 was taken outside the largest high school in Los Angeles just after Winter sports practice let out, and that you confined the sample to female students. As those basketball and volleyball players streamed past, how good an estimate would you get of the average female height globally?

That’s how I think of both the 19 th century US data I collected and the international data I drew from others: as expanding the sample size of stock and bond returns beyond what could be glimpsed from Ibbotson’s Stocks, Bonds, Bills & Inflation yearbook.

The expansion in size is greatest for longer holding periods. There are, after all, only 10 separate decade samples in a century, and only five independent two-decade samples. Once you have two centuries and 20 markets, there are 400 separate market-decades, and 200 distinct 20-year cases.

It should come as no surprise that the international sample included measurably worse stock market outcomes than anything seen in the post-1926 United States.

That’s an expected outcome from expanding the sample size. It says nothing about the future results that might be obtained from an investment in international stocks.

If you liked this post, don’t forget to subscribe to the  Enterprising Investor .

All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: ©Getty Images / Ascent / PKS Media Inc.

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Edward F. McQuarrie

Edward F. McQuarrie, Ph.D., is Professor Emeritus at the Leavey School of Business at Santa Clara University. After retiring from Santa Clara in 2016, he pursued new research interests in financial market history and retirement income planning. Projects under way include errors of estimate in historical index returns, the fitful nature of size and value effects, fluctuations in the corporate bond premium, the annuity wager, and payoff analyses for Roth conversions. Working papers describing his research in progress can be downloaded at https://ssrn.com/author=340720. For more information, visit his website at edwardfmcquarrie.com. He posts regularly at bogleheads.org and occasionally at medium.com.

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Once again, (1) Don’t try to time the market. (2)Timing is everything.

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At 70, Cyndi Lauper Has Nothing Left to Prove

She’s plotting a farewell tour. She’s starring in a documentary about her life. And she could only ever be herself.

At 70, Cyndi Lauper is charging back to action with a road show and “Let the Canary Sing,” a film that tells her life story. Credit... Thea Traff for The New York Times

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By Amanda Hess

• June 4, 2024

One Friday afternoon in May, Cyndi Lauper stepped out of her Upper West Side apartment building and into the streets of New York City. She wore glitter-encrusted glasses, sneakers with rainbow soles and a stack of beaded bracelets on each arm. A rice-paper parasol swung in her hand. As she walked, she examined the crowds and remarked when glints of interest caught her eye.

“Of course, up here it’s fashion hell,” she allowed of her tony neighborhood. And yet, every few blocks she rubbernecked at another woman’s look, her famous New Yawk accent lifting and tumbling in pleasure at what she saw:

“Look at these dames, how cute are they?”

“Did you love those pants? I kind of loved those pants.”

“Look at this lady,” she said, stepping off the curb and clocking a passerby. The woman moved nimbly, tomato-red streak in her silver hair, body draped in shades of fuchsia and cherry as she pushed the gleaming metal frame of a walker. “Fabulous,” Lauper exclaimed. “Come on!”

At 70, the pop icon and social justice activist isn’t just charging back into the streets. On Monday, Lauper announced her final tour, the Girls Just Wanna Have Fun Farewell Tour, which will have her headlining arenas across North America from late October to early December. And “Let the Canary Sing,” a documentary about her life and career that premiered at the Tribeca Festival last year, is streaming on Paramount+.

Lauper has not staged a major tour — “a proper tour, that’s mine” — in over a decade. But now her window of opportunity is closing, so she’s leaping through it. “I don’t think I can perform the way I want to in a couple of years,” she said. “I want to be strong.”

And until recently, when she finally agreed to sit for the director Alison Ellwood, she could not envision committing her life story to film. “I wasn’t going to do a documentary because I’m not dead,” she said. More to the point, she did not feel particularly misunderstood. From the moment she danced across the city in the 1983 video for “Girls Just Want to Have Fun,” she felt that she had articulated precisely what she wanted to say.

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