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What Is Formulation of Hypothesis in Research? Key Concepts and Steps

Formulating a hypothesis is a crucial part of any research project. It acts like a roadmap, guiding the direction of the study. By making a prediction based on existing knowledge, researchers can design experiments and collect data to test their ideas. This article will explore the key concepts and steps involved in creating a solid hypothesis.

Key Takeaways

• A hypothesis is a prediction that guides the research process.
• Formulating a hypothesis helps focus data collection and analysis.
• Background research is essential for developing a good hypothesis.
• There are different types of hypotheses, like null and alternative.
• Ethical considerations are important when making a hypothesis.

Understanding the Concept of Hypothesis in Research

A hypothesis is a statement that predicts what you expect to find in your research. It is a testable statement that explains what is happening or observed. The hypothesis proposes the relationship between the various participating variables. In scientific research, a hypothesis must meet certain criteria to be considered acceptable. If a hypothesis is disregarded, the research may be rejected by the scientific community.

Importance of Hypothesis Formulation in Research

Guiding the research process.

Formulating a hypothesis is crucial as it guides the entire research process . It provides a clear direction and helps you stay focused on your research objectives. By having a hypothesis, you can systematically plan your study and ensure that every step is aligned with your research goals.

Providing a Focus for Data Collection

A well-defined hypothesis helps in determining what data needs to be collected. It acts as a blueprint, ensuring that you gather relevant information that directly addresses your research question. This focused approach not only saves time but also enhances the efficiency of your research.

Facilitating Data Analysis

When you have a hypothesis, it simplifies the data analysis process. You can use statistical methods to test your hypothesis and draw meaningful conclusions. This is particularly important in hypothesis testing , where you assess the validity of your assumptions based on the collected data.

Investigating Background Research

Reviewing existing literature.

Before you start your research, it's crucial to review existing literature . This step helps you understand what has already been studied and where there might be gaps. You can use various sources like books, academic journals, and online databases. Knowing how to find literature efficiently will save you time and effort.

Identifying Research Gaps

Once you've reviewed the literature, the next step is identifying research gaps . These are areas that haven't been explored yet or need further investigation. Recognizing these gaps can inspire focused and relevant research questions. Discussing your ideas with peers or mentors can also help refine your questions.

Formulating Research Questions

After identifying the gaps, you can start formulating your research questions . These questions should be specific and feasible. They will guide your entire research process, from data collection to analysis. A well-defined research question is the foundation of a strong research proposal .

Developing a Theoretical Framework

A [ theoretical framework provides the theoretical assumptions](https://resources.nu.edu/c.php?g=1109615&p=10328334) for the larger context of a study, and is the foundation or 'lens' by which a study is developed. It helps you understand the theories related to your research topic and integrate them into your hypothesis formulation. This framework must demonstrate an understanding of theories and concepts that are relevant to the topic of your research paper and that relate to your study's objectives. Creating an effective theoretical framework involves establishing a research design aligned with objectives , ensuring quality and rigor in data collection.

Steps in Formulating a Hypothesis

Formulating a hypothesis is a crucial step in the research process. It involves several key steps that help in shaping a clear and testable statement. Each step is essential for ensuring that your hypothesis is well-founded and researchable.

Identifying Variables

The first step in formulating a hypothesis is identifying the variables involved in your study. Variables are the elements that you will measure, manipulate, or control in your research. These can be classified into independent variables (which you manipulate) and dependent variables (which you measure). Understanding the difference between these variables is fundamental to demystifying research .

Establishing Relationships Between Variables

Once you have identified your variables, the next step is to establish the relationships between them. This involves determining how the independent variable might affect the dependent variable. This step is crucial for creating clear statements and focusing on specific research questions. It is important to distinguish and formulate clear objectives in research to ensure that your hypothesis is testable.

Predicting Outcomes

The final step in formulating a hypothesis is predicting the outcomes of your research. This involves making an educated guess about what you expect to happen during your experiment. This step is often referred to as stating your hypothesis . Your prediction should be based on existing literature and theoretical frameworks related to your research topic. This is crucial for informed decision-making in research and helps in designing experiments to test hypotheses effectively.

Types of Hypotheses in Research

When conducting research, you will encounter various types of hypotheses, each serving a unique purpose in guiding your investigation . Understanding these types will help you formulate your own hypotheses more effectively.

Testing the Hypothesis

Testing hypotheses is a crucial part of research. It’s where you see if your ideas hold up in the real world. Good clinical research starts from a plausible hypothesis supported by contemporary scientific knowledge that makes a testable prediction. Let's explore the main steps in hypothesis testing:

Common Challenges in Hypothesis Formulation

When formulating a hypothesis, it's crucial to remain objective. Bias can skew your results and lead to incorrect conclusions. To avoid this, challenge your assumptions and evaluate how likely they are to affect your decisions and actions .

Creating untestable hypotheses is a common pitfall. Hypotheses that can't be empirically tested, either due to abstract constructs or lack of measurement methods, pose significant challenges. Ensure all variables can be measured or manipulated with existing research methods.

Research often involves complex variables that can be difficult to define and measure. Clearly operationalize abstract concepts and consider the feasibility of empirical testing during the hypothesis formulation stage .

Examples of Hypotheses in Various Research Fields

Hypotheses in social sciences.

In social sciences, hypotheses often explore relationships between social behaviors and societal factors. For instance, a hypothesis might state that increased social media use leads to higher levels of anxiety among teenagers. This type of hypothesis helps in understanding complex social dynamics and can guide interventions.

Hypotheses in Natural Sciences

Natural sciences frequently use hypotheses to explain natural phenomena. For example, a hypothesis in biology might propose that [a specific gene affects flower color ](https://www.examples.com/english/hypothesis.html), predicting that altering this gene will change the flower's hue. Such hypotheses are crucial for advancing scientific knowledge and can lead to significant discoveries.

Hypotheses in Applied Sciences

In applied sciences, hypotheses are often practical and solution-oriented. An example could be hypothesizing that a new type of renewable energy source will reduce carbon emissions more effectively than current methods. These hypotheses drive innovation and can result in real-world applications that address pressing issues.

Ethical Considerations in Hypothesis Formulation

Ensuring integrity and honesty.

When formulating a hypothesis, it is crucial to maintain integrity and honesty . This means you should honestly report data, results, methods, and procedures . Avoid manipulating data to fit your hypothesis, as this compromises the validity of your research. Remember, both the question and the hypothesis should be formulated before the study is planned and should not be generated retrospectively based on data .

Avoiding Plagiarism

Plagiarism is a serious ethical violation in research. Always give proper credit to the original authors of the ideas and findings you use. This not only respects the intellectual property of others but also upholds the academic standards of your work. Ethical considerations in Ph.D. thesis research are essential for protecting participants' rights, maintaining integrity, and upholding academic standards .

Respecting Confidentiality

Respecting the confidentiality of your research participants is paramount. Ensure that personal information is kept secure and used only for the purposes of your study. This is especially important when dealing with sensitive data. Ethical considerations and unforeseen variables in experimental research emphasize integrity, transparency, and adaptability .

When forming a hypothesis, it's crucial to think about the ethical side of things. This means making sure your research is fair and honest. If you're a student struggling with this, don't worry! Our Thesis Action Plan can guide you through every step. Visit our website to learn more and get started today.

In summary, formulating a hypothesis is a crucial step in the research process. It involves investigating background research, developing a theory, and determining how to test it. This process helps researchers make predictions and guide their studies. By following these steps, researchers can create testable hypotheses that provide a clear direction for their work. Understanding how to formulate a hypothesis is essential for conducting effective and meaningful research.

Frequently Asked Questions

What are the steps in formulating a hypothesis.

To form a hypothesis, researchers usually follow these steps: 1. Investigate background research in the area of interest. 2. Develop or examine a theory. 3. Decide how the theory will be tested and predict what the researcher expects to find based on previous studies.

Why is formulating a hypothesis important in research?

Formulating a hypothesis is crucial because it guides the research process, provides a focus for data collection, and makes it easier to analyze data.

What is a hypothesis in research?

A hypothesis is a predictive statement about what the researcher expects to find when testing the research question. It is based on background research and theories.

What are the characteristics of a good hypothesis?

A good hypothesis should be clear, testable, and based on existing theories or knowledge. It should also be specific and focused on a particular relationship between variables.

What are the different types of hypotheses in research?

There are several types of hypotheses, including null hypotheses, alternative hypotheses, and directional vs. non-directional hypotheses.

How do researchers test a hypothesis?

Researchers test a hypothesis by designing experiments, collecting data, and analyzing the results to see if they support the hypothesis.

What challenges do researchers face when formulating a hypothesis?

Common challenges include avoiding bias, ensuring the hypothesis is testable, and dealing with complex variables.

What ethical considerations are involved in formulating a hypothesis?

Researchers must ensure integrity and honesty, avoid plagiarism, and respect confidentiality when formulating a hypothesis.

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A concise guide to reproducible research using secondary data

Chapter 2 formulating a hypothesis.

“There is no single best way to develop a research idea.” ( Pischke 2012 )

2.1 How do you develop a research question and formulate a hypothesis?

You decide to undertake a scientific project. Where do you start? First, you need to find a research question that interests you and formulate a hypothesis. We will introduce some key terminology, steps you can take, and examples how to develop research questions. Note that .

What if someone assigns a topic to me? For students attending undergraduate and graduate courses that often pick topics from a list, all of these steps are equally important and necessary. You still need to formulate a research question and a hypothesis. And it is important to clarify the relevance of your topic for yourself.

When thinking about a research question, you need to identify a topic that is:

• Relevant , important in the world and interesting to you as a researcher: Does working on the topic excites you? You will spend many hours thinking about it and working on it. Therefore, it should be interesting and engaging enough for you to motivate your continued work on this topic.
• Specific : not too broad and not too narrow
• Feasible to research within a given time frame: Is it possible to answer the research question based on your time budget, data and additional resources.

How do you find a topic or develop a feasible research idea in the first place? Finding an idea is not difficult, the critical part is to find a good idea. How do you do that? There is no one specific way how one gets an idea, rather there is a myriad of ways how people come up with potential ideas (for example, as stated by Varian ( 2016 ) ).

You can find inspiration by

• Looking at insights from the world around you: your own life and experiences, observe the behavior of people around you
• Talking to people around you, experts, other students, family members
• Talking to individuals outside your field (non-economists)
• Talking to professionals working in the area you are interested in (you may use social media and professional platforms like LinkedIN or Twitter to make contact)
• Reading journal articles from other non-economic social sciences and the medical literature
• What are the issues being discussed?
• How do these issues affect people’s lives?

In addition you could

• Go to virtual and in-person seminars, for example, the Essen Health Economics Seminar
• Look at abstracts of scientific articles and working papers
• Look at the literature in a specific field you are interested in, for example, screening complete issues of journals or editorials about certain research advancements. By reading this literature you might come up with the idea on how to extend and refine previous research.

Once you identified a research question that is of interest to you, you need to define a hypothesis.

2.2 What is a hypothesis?

A hypothesis is a statement that introduces your research question and suggests the results you might find. It is an educated guess. You start by posing an economic question and formulate a hypothesis about this question. Then you test it with your data and empirical analysis and either accept or reject the hypothesis. It constitutes the main basis of your scientific investigation and you should be careful when creating it.

2.2.1 Develop a hypothesis

Before you formulate your hypothesis, read up on the topic of interest. This should provide you with sufficient information to narrow down your research question. Once you find your question you need to develop a hypothesis, which contains a statement of your expectations regarding your research question’s results. You propose to prove your hypothesis with your research by testing the relationship between two variables of interest. Thus, a hypothesis should be testable with the data at hand. There are two types of hypotheses: alternative or null. Null states that there is no effect. Alternative states that there is an effect.

There is an alternative view on this that suggests one should not look at the literature too early on in the idea-generating process to not be influenced and shaped by someone else’s ideas ( Varian 2016 ) . According to this view you can spend some time (i.e. a few weeks) trying to develop your own original idea. Even if you end up with an idea that has already been pursued by someone else, this will still provide you with good practice in developing publishable ideas. After you have developed an idea and made sure that it was not yet investigated in the literature, you can start conducting a systematic literature review. By doing this, you can find some other interesting insights from the work of others that you can synthesize in your own work to produce something novel and original.

2.2.2 Identify relevant literature

For your research project you will need to identify and collect previous relevant literature. It should involve a thorough search of the keywords in relevant databases and journals. Place emphasis on articles from high-ranking journals with significant numbers of citations. This will give you an indication of the most influential and important work in the field. Once you identify and collect the relevant literature for your topic, you will need to critically synthesize it in your literature review.

When you perform your literature review, consider theories that may inform your research question. For example, when studying physician behavior you may consider principal-agent theory.

2.2.3 Research question or literature review: the chicken or the egg problem?

Whether you start reading the literature first or by developing an idea may depend on your level (graduate student, early career researcher) and other goals. However, thinking freely about what you like to investigate first may help to critically develop a feasible and interesting research question.

We highlight an example how to start with investigating the real world and subsequently posing a research question ( “How to Write a Strong Hypothesis Steps and Examples ” 2019 ; “Developing Strong Research Questions Criteria and Examples ” 2019 ; Schilbach 2019 ) . For example, based on your observation you notice that people spend extensive amount of time looking at their smartphones. Maybe even you yourself engage in the same behavior. In addition, you read a BBC News article Social media damages teenagers’ mental health, report says .

(#fig:social_media)Social media and mental health

Source: BBC

You decide to translate this article and your observations into a research question : How does social media use affect mental health? Before you formulate your hypothesis, read up on the topic of interest. Read economic, medical and other social science literature on the topic. There is likely to be a vast amount of literature from non-economic fields that are doing research on your topic of interest, for example, psychology or neuroscience. Familiarize yourself with it and master it. Do not get distracted by different scientific methodologies and techniques that might seem not up-to-par to the economic studies (small sample sizes, endogeneity, uncovering association rather than causation, etc.), but rather focus on suggestions of potential mechanisms.

A hypothesis is then your research question distilled into a one sentence statement, which presents your expectations regarding the results. You propose to prove your hypothesis by testing the relationship between two variables of interest with the data at hand. There are two types of hypotheses: alternative or null. The null hypothesis states that there is no effect. The alternative hypothesis states that there is an effect.

A hypothesis related to the above-stated research question could be: The increased use of social media among teenagers leads to (is associated with) worse mental health outcomes, i.e. increased incidence of depression, eating disorders, worse well-being and lower self-esteem. It suggests a direction of a relationship that you expect to find that is guided by your observations and existing evidence. It is testable with scientific research methods by using statistical analysis of the relevant data.

Your hypothesis suggests a relationship between two variables: social media use (your independent variable \(X\) ) and mental health (dependent variable \(Y\) ). It could be framed in terms of correlation (is associated with) or causation (leads to). This should be reflected in the choice of scientific investigation you decide to undertake.

The null hypothesis is: There is no relationship between social media use among teenagers and their mental health .

2.3 Resources box

2.3.1 how to develop strong research questions.

• The form of the research process
• Varian, H. R. (2016). How to build an economic model in your spare time. The American Economist, 61(1), 81-90.

2.3.2 Identify relevant literature from major general interest and field literature

To identify the relevant literature you can

• use academic search engines such as Google Scholar, Web of Science, EconLit, PubMed.
• search working paper series such as the National Bureau of Economic Research , NetEc or IZA
• search more general resource sites such as Resources for Economists
• go to the library/use library database

2.3.3 Assess the quality of a journal article

Several rankings may help to assess the quality of research you consider

• Journals of general interest and by field in economics and management - For German-speaking countries, consider the VWL / BWL Handelsblatt Ranking for economics and management - The German Association of Management Scholars provides an expert-based ranking VHB JourQual 3.0, Teilranking Management im Gesundheitswesen - Web of Science Impact Factors - Scimago
• Health Economics, Health Services and Health Care Managment Research: Health Economics Journals List
• Be aware that like in any other domain there are predatory publishing practices .

Use tools to investigate how a journal article is connected to other works

• Citationgecko
• Connected papers
• scite_ – a tool to get a first impression whether a study is disputed or academic consensus

2.3.4 Organize your literature

• Zotero (free of charge)
• Mendeley (free of charge)
• EndNote (potentially free of charge via your university)
• Citavi (potentially free of charge via your university)
• BibTEX if you work with TEX
• Excel spread sheet

2.4 Checklist to get started with formulating your hypothesis

• Find an interesting and relevant research topic, if not assigned
• Try to suck up all information you can easily obtain from various sources within and outside academic literature
• Formulate one compelling research question
• Find the best available empirical and theoretical evidence that is related to your research question
• Formulate a hypothesis
• Check whether data are available for analysis
• Challenge your idea with your fellows or senior researchers

2.5 Example: Hellerstein ( 1998 )

As an illustration of the research process of formulating a hypothesis, designing a study, running a study, collecting and analyzing the data and, finally, reporting the study, we provide an example by replicating Judith K. Hellerstein’s paper “The Importance of the Physician in the Generic versus Trade-Name Prescription Decision” that was published in 1998 in the RAND Journal of Economics.

Hellerstein’s 1998 paper has impacted discussion about behavioral factors of physician decisions and pharmaceutical markets over two decades. The study received 448 citations on Google Scholar since 1998 by 27/03/2022, including recent mentions in top field journals such as Journal of Public Economics (2021) , Journal of Health Economics (2019) , and Health Economics (2019) .

Figure 2.1: Connected graph of Hellerstein ( 1998 ) , February 2022

Figure 2.1 shows a connected graph of prior and derivative works related to the study.

The work has impacted the literature researching the role of physician behavior and its influence on access, adoption and diffusion of health services, moral hazard and incentives in prescription and treatment decisions and the influence of different payment schemes, and a vast body of literature studying the pharmaceutical market.

The research that has been influenced by Hellerstein includes evidence on:

• generic drug entries and market efficiency
• the effectiveness of pharmaceutical promotion
• the effectiveness of price regulations
• the role of patents and dynamics of market segmentation

At the end of each chapter, we demonstrate insights into this study that we replicate.

2.5.1 Context of the study - escalating health expenditures

In the United States, the total prescription drug expenditure in 2020 marked about 358.7 billion US Dollars ( Statista n.d. ) . The prescription of generic drugs in comparison to more expensive brand-name versions is an option in reducing the total health care expenditure. Generic drugs are bioequivalent in the active ingredients and can serve as a channel to contain prescription expenditure ( Kesselheim 2008 ) as generic drugs are between 20 and 90% cheaper than their trade-name alternatives ( Dunne et al. 2013 ) .

2.5.2 Research question - How does a patient’s insurance status influence the physician’s choice between generic compared to brand-name drugs?

Physicians are faced with a multitude of medication options, including the choice between generic and trade-name drugs. Physicians ideally act as agents for their patients to identify the best available treatment option based on their needs. Choosing the best treatment entails cost of coordination and cognition. The prescription of generic drugs may serve as an example to what extent physicians customize treatments according to patients’ needs with regards to cost. From an economic point of view we may expect that once a generic drug is available, a perfectly rational agent (i.e. physician) would prescribe a generic drug instead of the trade-name version if therapeutically identical ( Dranove 1989 ) . This leads to the following research question: “Do physicians vary their prescription decisions on a patient-by-patient basis or do they systematically prescribe the same version, trade-name or generic, to all patients?” .

The 1998 Hellerstein’s study examines two hypotheses:

• The physician prescribing choice influences the selection of a generic over a brand-name drug
• The patient’s insurance status influences the physician’s choice between generic and brand-name drugs.

For the purpose of this example and in the replication exercise we focus on the second aspect.

2.5.3 Hypothesis

The paper formulates the following hypothesis:

Physicians are more likely to prescribe generics to patients who do not have insurance coverage for prescription pharmaceuticals (moral hazard in insurance)

Hellerstein ( 1998 ) discusses that, based on insurance status, some patients may demand certain care more than others. If, for example, the prescription drug is reimbursed by the patient’s health insurance, this may cause overconsumption. This behavior can potentially differ by the patient’s insurance scheme. A patient that has no insurance and, thus, does not get any reimbursement for prescription drugs, might have a higher incentive to demand cheaper generic drugs ( Danzon and Furukawa 2011 ) than a patient with insurance that covers prescription drugs, either generic or trade-name. Given that the United States have different insurance schemes with varying prescription drug coverage, it is of interest to investigate the role of a patient’s insurance status in the physician’s choice between generic compared to brand-name drugs.

Hellerstein ( 1998 ) considers a patient’s insurance status as a matter of dividing the study population in groups for which the choice between generic and brand-name drugs differs. She suggests that There is a relationship between the prescription of a generic drug and insurance status of a patient. ( Hellerstein 1998 ) .

Providing answers to a research question requires formulating and testing a hypothesis. Based on logic, theory or previous research, a hypothesis proposes an expected relationship within the given data. According to her research question, Hellerstein hypothesizes that: Physicians are more likely to prescribe generics to patients who do not have insurance coverage for prescription pharmaceuticals.

Specifically, she writes “if there is moral hazard in insurance when it comes to physician prescription behavior, there will be differences in the propensity of physicians to prescribe low-cost generic drugs, and these differences will be (partially) a function of the insurance held by the patient. In particular, if moral hazard exists, patients with extensive insurance coverage for prescription drugs (like those on Medicaid in 1989) should receive prescriptions written for generic drugs less frequently than patients with no prescription drug coverage.” ( Hellerstein 1998, 113 )

Based on Hellerstein’s considerations, we expect the effect of the insurance status on whether a patient receives a generic to be different from zero. To obtain a testable null hypothesis, we reformulate this relationship so that we reject the hypothesis if our expectations are correct. This means, if we expect to see an effect of insurance on prescriptions of generics, our null hypothesis is that insurance status has no effect on the outcome (prescription of generic drugs). No moral hazard arises from having obtained insurance.

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Hypothesis Testing | A Step-by-Step Guide with Easy Examples

Published on November 8, 2019 by Rebecca Bevans . Revised on June 22, 2023.

Hypothesis testing is a formal procedure for investigating our ideas about the world using statistics . It is most often used by scientists to test specific predictions, called hypotheses, that arise from theories.

There are 5 main steps in hypothesis testing:

• State your research hypothesis as a null hypothesis and alternate hypothesis (H o ) and (H a  or H 1 ).
• Collect data in a way designed to test the hypothesis.
• Perform an appropriate statistical test .
• Decide whether to reject or fail to reject your null hypothesis.
• Present the findings in your results and discussion section.

Though the specific details might vary, the procedure you will use when testing a hypothesis will always follow some version of these steps.

Table of contents

Step 1: state your null and alternate hypothesis, step 2: collect data, step 3: perform a statistical test, step 4: decide whether to reject or fail to reject your null hypothesis, step 5: present your findings, other interesting articles, frequently asked questions about hypothesis testing.

After developing your initial research hypothesis (the prediction that you want to investigate), it is important to restate it as a null (H o ) and alternate (H a ) hypothesis so that you can test it mathematically.

The alternate hypothesis is usually your initial hypothesis that predicts a relationship between variables. The null hypothesis is a prediction of no relationship between the variables you are interested in.

• H 0 : Men are, on average, not taller than women. H a : Men are, on average, taller than women.

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For a statistical test to be valid , it is important to perform sampling and collect data in a way that is designed to test your hypothesis. If your data are not representative, then you cannot make statistical inferences about the population you are interested in.

There are a variety of statistical tests available, but they are all based on the comparison of within-group variance (how spread out the data is within a category) versus between-group variance (how different the categories are from one another).

If the between-group variance is large enough that there is little or no overlap between groups, then your statistical test will reflect that by showing a low p -value . This means it is unlikely that the differences between these groups came about by chance.

Alternatively, if there is high within-group variance and low between-group variance, then your statistical test will reflect that with a high p -value. This means it is likely that any difference you measure between groups is due to chance.

Your choice of statistical test will be based on the type of variables and the level of measurement of your collected data .

• an estimate of the difference in average height between the two groups.
• a p -value showing how likely you are to see this difference if the null hypothesis of no difference is true.

Based on the outcome of your statistical test, you will have to decide whether to reject or fail to reject your null hypothesis.

In most cases you will use the p -value generated by your statistical test to guide your decision. And in most cases, your predetermined level of significance for rejecting the null hypothesis will be 0.05 – that is, when there is a less than 5% chance that you would see these results if the null hypothesis were true.

In some cases, researchers choose a more conservative level of significance, such as 0.01 (1%). This minimizes the risk of incorrectly rejecting the null hypothesis ( Type I error ).

The results of hypothesis testing will be presented in the results and discussion sections of your research paper , dissertation or thesis .

In the results section you should give a brief summary of the data and a summary of the results of your statistical test (for example, the estimated difference between group means and associated p -value). In the discussion , you can discuss whether your initial hypothesis was supported by your results or not.

In the formal language of hypothesis testing, we talk about rejecting or failing to reject the null hypothesis. You will probably be asked to do this in your statistics assignments.

However, when presenting research results in academic papers we rarely talk this way. Instead, we go back to our alternate hypothesis (in this case, the hypothesis that men are on average taller than women) and state whether the result of our test did or did not support the alternate hypothesis.

If your null hypothesis was rejected, this result is interpreted as “supported the alternate hypothesis.”

These are superficial differences; you can see that they mean the same thing.

You might notice that we don’t say that we reject or fail to reject the alternate hypothesis . This is because hypothesis testing is not designed to prove or disprove anything. It is only designed to test whether a pattern we measure could have arisen spuriously, or by chance.

If we reject the null hypothesis based on our research (i.e., we find that it is unlikely that the pattern arose by chance), then we can say our test lends support to our hypothesis . But if the pattern does not pass our decision rule, meaning that it could have arisen by chance, then we say the test is inconsistent with our hypothesis .

If you want to know more about statistics , methodology , or research bias , make sure to check out some of our other articles with explanations and examples.

• Normal distribution
• Descriptive statistics
• Measures of central tendency
• Correlation coefficient

Methodology

• Cluster sampling
• Stratified sampling
• Types of interviews
• Cohort study
• Thematic analysis

Research bias

• Implicit bias
• Cognitive bias
• Survivorship bias
• Availability heuristic
• Nonresponse bias
• Regression to the mean

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.

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).

Null and alternative hypotheses are used in statistical hypothesis testing . The null hypothesis of a test always predicts no effect or no relationship between variables, while the alternative hypothesis states your research prediction of an effect or relationship.

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Quantitative Research in Mass Communications : R and RStudio

7 formulating research questions and hypotheses, 7.1 introduction to research questions and hypotheses.

In the realm of academic research, particularly within the field of mass communications, the formulation of research questions and hypotheses is a foundational step that sets the direction and scope of a study. These elements are crucial not only for guiding the research process but also for defining the study’s objectives and expectations. This section highlights the significance of research questions and hypotheses and elucidates the role they play in framing a study.

The Importance of Research Questions and Hypotheses in Guiding Research

Defining the Research Focus: Research questions serve as the cornerstone of any study, clearly outlining the specific issue or phenomenon that the research aims to explore. They help narrow down the broad area of interest into a focused inquiry that can be systematically investigated.

Guiding Methodology: The nature of the research question—whether it seeks to describe, compare, or determine cause and effect—directly influences the choice of research design, methods, and analysis techniques. Well-formulated questions ensure that the research methodology is appropriately aligned with the study’s objectives.

Facilitating Hypothesis Formulation: In quantitative research, hypotheses often stem from the research questions, proposing specific predictions or expectations based on theoretical foundations or previous studies. Hypotheses provide a testable statement that guides the empirical investigation and analysis.

7.1.1 Overview of the Role These Elements Play in Framing a Study

Structuring the Research Framework: Together, research questions and hypotheses establish the conceptual framework for a study, defining its boundaries and specifying the variables of interest. This framework serves as a blueprint, guiding all subsequent steps of the research process.

Informing Literature Review: Research questions and hypotheses inform the scope and focus of the literature review, directing attention to relevant theories, concepts, and empirical findings. This ensures that the review is tightly integrated with the study’s aims and contributes to building a solid theoretical foundation.

Determining Data Collection and Analysis: The formulation of research questions and hypotheses has direct implications for data collection methods, sampling strategies, and analytical techniques. They dictate what data are needed, how they should be collected, and the statistical tests or analytical approaches required to address the research questions and test the hypotheses.

Communicating the Study’s Purpose: Research questions and hypotheses effectively communicate the purpose and direction of the study to the academic community, stakeholders, and the broader public. They articulate the study’s contribution to knowledge, its relevance to theoretical debates or practical issues, and the potential implications of the findings.

In summary, research questions and hypotheses are indispensable components of the research process, serving as the guiding light for the entire study. They provide clarity, direction, and purpose, ensuring that the research is coherent, focused, and methodologically sound. By meticulously crafting these elements, researchers in mass communications lay the groundwork for meaningful and impactful studies that advance our understanding of complex media landscapes and communication dynamics.

7.2 Understanding Research Questions

Research questions are the foundation of any scholarly inquiry, guiding the direction and focus of the study. In mass communications research, where topics can range from analyzing media effects to understanding audience behaviors, formulating effective research questions is crucial for defining the scope and objectives of a study. This section delves into the definition and characteristics of a good research question, distinguishes between exploratory and descriptive research questions, and discusses strategies for developing clear and focused questions.

Definition and Characteristics of a Good Research Question

Definition: A research question is a clearly formulated question that outlines the issue or problem your study aims to address. It sets the stage for the research design, data collection, and analysis, directing the inquiry toward a specific goal.

Characteristics of a Good Research Question:

• Clarity: It should be clearly stated, avoiding ambiguity and ensuring that the research focus is understandable to others.
• Relevance: The question should be significant to the field of study, addressing gaps in the literature or emerging issues in mass communications.
• Researchability: It must be possible to answer the question through empirical investigation, using available research methods and tools.
• Specificity: A good question is specific, targeting a particular aspect of the broader topic to make the research manageable and focused.

Distinction Between Exploratory and Descriptive Research Questions

Exploratory Research Questions: These questions are used when little is known about the topic or phenomenon. Exploratory questions aim to investigate and gain insights into a subject, seeking to understand how or why something happens. In mass communications, an exploratory question might ask, “How do emerging social media platforms influence political engagement among young adults?”

Descriptive Research Questions: Descriptive questions aim to describe the characteristics or features of a subject. They are used when the goal is to provide an accurate representation or count of a phenomenon. A descriptive research question in mass communications might be, “What are the predominant themes in news coverage of environmental issues?”

Developing Clear and Focused Research Questions

• Specificity: Your research question should be narrowly tailored to address a specific issue within the broader field of mass communications. This specificity helps in defining the study’s scope and focusing the research efforts.
• Feasibility: Consider the practical aspects of answering your research question, including the availability of data, time constraints, and resource limitations. A feasible question is one that can be realistically investigated within the parameters of your study.
• Literature Review: Conduct a thorough review of existing research to identify gaps or unresolved questions in the field. This can inspire focused and relevant research questions.
• Consultation: Discuss your ideas with peers, mentors, or experts in mass communications. Feedback can help refine your questions and ensure they are both specific and feasible.
• Pilot Studies: Small-scale pilot studies or preliminary investigations can provide insights that help in formulating or refining your research questions.

Crafting clear and focused research questions is a critical step in the research process, setting the stage for meaningful and impactful inquiry. By ensuring that your questions are specific, feasible, and relevant to the field of mass communications, you lay the groundwork for a study that can contribute valuable insights to our understanding of media and communication phenomena.

7.3 Types of Research Questions

In the pursuit of scientific inquiry within mass communications, research questions serve as the navigational compass guiding the research process. These questions can be broadly categorized into two types: nondirectional and directional. Each type serves a distinct purpose and is formulated based on the nature of the study and the specific objectives the researcher aims to achieve. This section explores the definitions, uses, and strategies for crafting both nondirectional and directional research questions.

Nondirectional Research Questions

Definition: Nondirectional research questions are open-ended queries that explore the existence of a relationship between variables without specifying the anticipated direction of this relationship. They are used when the literature does not strongly suggest which outcome is expected or when exploring new or under-researched areas.

When to Use Them: Employ nondirectional questions when previous research is inconclusive, conflicting, or absent. They are particularly useful in exploratory studies where the aim is to uncover patterns, relationships, or phenomena without presupposing outcomes.

Crafting Questions:

• Focus on Exploration: Phrase your question to emphasize exploration, such as “Is there a relationship between social media usage and political participation among young adults?”
• Avoid Implied Direction: Ensure the wording does not inadvertently suggest a presumed direction of the relationship. The question should remain open to any outcome, whether positive, negative, or neutral.

Directional Research Questions

Definition: Directional research questions specify the expected direction of the relationship between variables. These questions are based on predictions that are often derived from theoretical frameworks or existing literature.

Purposes: Directional questions are used when there is sufficient theoretical or empirical basis to hypothesize a particular outcome. They guide the research towards testing specific hypotheses, making them suitable for studies aiming to confirm or refute theoretical predictions.

Formulating Questions:

• Specify Expected Outcomes: Clearly articulate the anticipated direction of the relationship in the question. For example, “Does increased exposure to environmental news lead to higher levels of environmental activism among viewers?”
• Ground in Literature: Ensure that the directionality implied by your question is supported by theoretical rationales or empirical evidence from previous research. This alignment strengthens the justification for expecting a particular outcome.

7.4 Strategies for Formulating Research Questions

Regardless of the type, crafting effective research questions requires a deep understanding of the topic at hand, a thorough review of the existing literature, and a clear articulation of the research’s goals. Here are some strategies to consider:

• Engage with Current Research: Immerse yourself in the latest studies and debates within the field of mass communications to identify trends, gaps, and areas ripe for investigation.
• Consult Theoretical Frameworks: Draw on established theories to guide the formulation of your questions, whether seeking to explore uncharted territory (nondirectional) or test specific propositions (directional).
• Iterative Refinement: Research questions often evolve during the initial stages of a study. Be prepared to refine your questions as you delve deeper into the literature and sharpen your study’s focus.

By thoughtfully selecting the type of research question that best suits the aims and scope of your study, you lay a solid foundation for a coherent, rigorous, and insightful exploration of mass communications phenomena.

7.5 Operationalization of Concepts

Operationalization is a critical process in the research design phase, particularly in quantitative studies within the realm of mass communications. It involves defining the abstract concepts or variables in measurable terms, determining how they will be observed, measured, or manipulated within the study. This section outlines the essence of operationalization, its pivotal role in research, the steps involved in operationalizing variables, and provides examples pertinent to mass communications research.

Defining Operationalization and Its Significance in Research

Definition: Operationalization is the process by which researchers define how to measure or manipulate the variables of interest in a study. It transforms theoretical constructs into measurable indicators, allowing for empirical observation and quantitative analysis.

Significance: The operationalization of concepts is fundamental to ensuring the reliability and validity of a study. By clearly specifying how variables are measured, researchers enable the replication of the study, enhance the clarity and coherence of their research design, and facilitate the objective analysis of findings.

Steps to Operationalize Variables

Identify the Key Concepts: Begin by clearly identifying the key concepts or variables you intend to study. In mass communications, this might include phenomena like media influence, audience engagement, or digital literacy.

Define the Variables Conceptually: Provide clear, conceptual definitions for each variable, drawing on existing literature or theoretical frameworks to delineate the boundaries of the concept.

Specify the Variables Operationally: Decide on the specific operations, techniques, or instruments you will use to measure or manipulate each variable. This includes determining the type of data to be collected, the scale of measurement, and the method of data collection.

Develop or Select Measurement Instruments: Choose or develop instruments that accurately measure your operationalized variables. This could involve creating surveys, designing experiments, or developing coding schemes for content analysis.

Pilot Test: Conduct a pilot test of your measurement instruments to ensure they effectively capture the operationalized variables. Adjustments based on feedback from the pilot test can improve the reliability and validity of the measures.

Examples of Operationalizing Common Variables in Mass Communications Research

Audience Engagement: Conceptually defined as the level of interaction and involvement an individual has with media content. Operationally, it could be measured through the number of social media shares, comments, or time spent viewing content.

Media Influence on Public Opinion: Conceptually, this refers to the impact media content has on shaping individuals’ attitudes and beliefs. Operationally, it could be measured by changes in attitudes before and after exposure to specific media messages, using pretest-posttest surveys.

Digital Literacy: Conceptually defined as the ability to find, evaluate, create, and communicate information using digital technologies. Operationally, digital literacy could be measured through a questionnaire assessing skills in these areas, with items rated on a Likert scale.

Operationalization is a cornerstone of rigorous research methodology, bridging the gap between theoretical concepts and empirical evidence. By meticulously defining and measuring variables, researchers in mass communications can ground their studies in observable reality, enhancing the validity of their findings and contributing meaningful insights into the complex dynamics of media and communication.

7.6 Developing Hypotheses

In the framework of quantitative research, particularly within the expansive field of mass communications, hypotheses serve as pivotal elements that further refine and operationalize the research questions. This section elucidates the definition and function of hypotheses in quantitative research, explores the relationship between research questions and hypotheses, and outlines the criteria that make a hypothesis testable.

Definition and Function of Hypotheses in Quantitative Research

Definition: A hypothesis is a predictive statement that proposes a possible outcome or relationship between two or more variables. It is grounded in theory or prior empirical findings and serves as a basis for scientific inquiry.

Function: The primary function of a hypothesis is to provide a specific, testable proposition derived from the broader research question. Hypotheses guide the research design, data collection, and analysis process, offering a clear focus for empirical investigation. They enable researchers to apply statistical methods to test the proposed relationships or effects, thereby contributing to the accumulation of scientific knowledge.

The Relationship Between Research Questions and Hypotheses

From Questions to Hypotheses: Research questions set the stage for the research by identifying the key phenomena or relationships of interest. Hypotheses take this a step further by specifying the expected direction or nature of these relationships based on theoretical or empirical groundwork. Essentially, while research questions identify “what” the study aims to explore, hypotheses propose “how” these explorations will unfold.

Complementarity: Research questions and hypotheses are complementary, with the former providing a broad inquiry framework and the latter offering a focused, conjectural answer that can be empirically tested. This synergy ensures that the research is both guided by curiosity and anchored in a framework that facilitates systematic investigation.

Criteria for a Testable Hypothesis

For a hypothesis to effectively contribute to the research process, it must be testable. The following criteria are essential for constructing a hypothesis that can be empirically evaluated:

Specificity: A testable hypothesis must clearly and specifically define the variables involved and the expected relationship between them. This clarity ensures that the hypothesis can be directly linked to observable and measurable outcomes.

Empirical Referents: The variables within the hypothesis must have empirical referents – that is, they must be capable of being measured or manipulated in the real world. This allows the hypothesis to be subjected to empirical testing.

Predictive Nature: A testable hypothesis should make a predictive statement about the expected outcome of the study, enabling the research to confirm or refute the proposed relationship or effect based on empirical evidence.

Grounding in Theory or Prior Research: The hypothesis should be grounded in existing theoretical frameworks or empirical findings, providing a rationale for the expected relationship or outcome. This grounding not only lends credibility to the hypothesis but also ensures that it contributes to the ongoing academic discourse.

Falsifiability: Finally, a testable hypothesis must be falsifiable. This means it should be possible to conceive of an outcome that would contradict the hypothesis, allowing for the possibility of it being disproven through empirical evidence.

Developing well-crafted hypotheses is a critical step in the quantitative research process, particularly in mass communications, where the rapid evolution of media technologies and platforms continually opens new avenues for inquiry. By adhering to these criteria, researchers can ensure that their hypotheses are not only testable but also meaningful, contributing valuable insights to our understanding of complex media landscapes and their impacts on society.

7.7 Types of Hypotheses

In the empirical research landscape, especially within the domain of mass communications, hypotheses are indispensable tools that guide the investigative process. They are typically categorized into null hypotheses and alternative hypotheses, each serving a distinct role in framing the research inquiry. This section provides definitions for these two types of hypotheses, discusses their roles in research, and offers guidance on formulating them effectively.

Null Hypotheses (H0)

Definition: The null hypothesis (H0) posits that there is no difference, effect, or relationship between the variables under investigation. It represents a statement of skepticism or neutrality, suggesting that any observed differences or relationships in the data are due to chance rather than a systematic effect.

Role in Research: The null hypothesis serves as a benchmark for testing the existence of an effect or relationship. By attempting to disprove or reject the null hypothesis through statistical analysis, researchers can provide evidence supporting the presence of a meaningful effect or relationship. The null hypothesis is foundational in hypothesis testing, enabling researchers to apply statistical methods to determine the likelihood that observed data could have occurred under the null condition.

Formulating Null Hypotheses: Null hypotheses are formulated as statements of no difference or no relationship. For example, in a study examining the impact of social media usage on political engagement, a null hypothesis might state, “There is no difference in political engagement levels between users and non-users of social media.”

Alternative Hypotheses (H1)

Definition: The alternative hypothesis (H1) is the counter proposition to the null hypothesis. It posits that there is a significant difference, effect, or relationship between the variables being studied. The alternative hypothesis reflects the researcher’s theoretical expectation or prediction about the outcome of the study.

Complementing Null Hypotheses: The alternative hypothesis directly complements the null hypothesis by specifying the expected effect or relationship that the research aims to demonstrate. While the null hypothesis posits the absence of an effect, the alternative hypothesis asserts its presence, guiding the direction of the study’s empirical investigation.

Crafting Alternative Hypotheses: Alternative hypotheses are crafted to predict specific outcomes based on the research question and theoretical framework. They should clearly articulate the anticipated direction or nature of the relationship or difference between variables. Continuing the earlier example, an alternative hypothesis might state, “Users of social media exhibit higher levels of political engagement than non-users.”

7.8 Strategic Formulation of Hypotheses

The formulation of null and alternative hypotheses is a strategic exercise that sets the stage for empirical testing. Effective hypotheses are:

• Specific and Concise: Clearly define the variables and the expected relationship or difference, avoiding ambiguity.
• Empirically Testable: Ensure that the hypotheses can be tested using available research methods and data.
• Theoretically Grounded: Base your hypotheses on existing literature, theories, or preliminary evidence, providing a rationale for the expected outcomes.

In mass communications research, where the interplay of media, technology, and society offers a rich tapestry of phenomena to explore, the thoughtful formulation of null and alternative hypotheses is crucial. It not only delineates the scope of the investigation but also ensures that the research contributes meaningful insights into the dynamics of communication processes and their impacts.

7.9 Directional and Nondirectional Hypotheses

In the nuanced world of quantitative research, particularly within the field of mass communications, hypotheses serve as a bridge between theoretical inquiry and empirical investigation. They are typically formulated as either directional or nondirectional, each with specific implications for the study’s design and analysis. This section clarifies the distinction between these two types of hypotheses and provides guidance on when to use each, complemented by examples from mass communications research.

Understanding the Distinction and When to Use Each Type

Directional Hypotheses: Directional hypotheses specify the expected direction of the relationship or difference between variables. They are based on theoretical predictions or empirical evidence suggesting a particular outcome. Directional hypotheses are used when prior research or theory provides a strong basis for anticipating the direction of the effect.

Nondirectional Hypotheses: Nondirectional hypotheses indicate that a relationship or difference exists between variables but do not specify the direction. They are appropriate when there is uncertainty about the expected outcome or when previous studies have yielded mixed or inconclusive results.

Examples of Both Directional and Nondirectional Hypotheses in Mass Communications Research

• “Individuals who frequently engage with news content on social media platforms will exhibit higher levels of political awareness than those who do not engage with news content on these platforms.” This hypothesis predicts a specific direction of the relationship between social media news engagement and political awareness.
• “Exposure to environmental documentaries will increase viewers’ concern for environmental issues more than exposure to traditional news coverage of the same issues.” This hypothesis specifies an expected difference in the effect of two types of media content on environmental concern.
• “There is a relationship between the frequency of smartphone use for social media and the level of social isolation experienced by young adults.” This hypothesis suggests a relationship exists but does not predict whether more frequent use increases or decreases social isolation.
• “The introduction of interactive digital learning tools in communication courses affects students’ academic performance.” This hypothesis indicates that an effect is expected but does not specify whether the effect is positive or negative on academic performance.

7.10 Deciding Between Directional and Nondirectional Hypotheses

The choice between directional and nondirectional hypotheses hinges on several factors:

• Theoretical Basis: Strong theoretical foundations or extensive empirical evidence supporting a specific outcome favor the use of directional hypotheses.
• Research Objectives: Exploratory studies aiming to identify patterns or relationships might initially employ nondirectional hypotheses, especially in emerging areas of mass communications where less is known.
• Statistical Considerations: Directional hypotheses allow for more focused statistical tests (e.g., one-tailed tests), which can be more powerful in detecting specified effects. However, they require a strong justification for predicting the direction of the effect.

By carefully considering these factors, researchers in mass communications can effectively choose the type of hypothesis that best suits their study’s objectives and theoretical framework. Whether directional or nondirectional, the formulation of hypotheses is a critical step in the research process, guiding empirical inquiry and contributing to the advancement of knowledge in the dynamic field of mass communications.

7.11 Criteria for Good Research Questions and Hypotheses

In the rigorous academic landscape of mass communications research, the construction of research questions and hypotheses serves as the bedrock upon which studies are built and conducted. These foundational elements not only guide the direction of the research but also determine its scope, focus, and potential contribution to the field. To ensure the effectiveness and integrity of research, certain criteria must be met. This section outlines the essential qualities of good research questions and hypotheses: clarity and precision, relevance to the field of study, and researchability with empirical testing potential.

Clarity and Precision

Definition: Clarity in research questions and hypotheses means that they are stated in a straightforward and unambiguous manner, easily understood by those within and outside the field. Precision involves the specific delineation of the variables and constructs involved, leaving no room for misinterpretation.

Importance: Clear and precise formulations allow for a focused investigation, guiding the research design, data collection, and analysis process. They ensure that the study addresses the intended concepts and relationships directly and effectively.

Strategies for Achieving Clarity and Precision:

• Use specific, defined terms and avoid jargon that may not be universally understood.
• Clearly specify the variables or phenomena being studied and their expected relationships.
• Ensure that hypotheses are directly testable, with defined criteria for confirmation or refutation.

Relevance to the Field of Study

Definition: Relevance implies that the research questions and hypotheses address significant issues, gaps, or debates within the field of mass communications. They should contribute to advancing understanding, theory, or practice in meaningful ways.

Importance: Research that is relevant to the field is more likely to receive attention from scholars, policymakers, and practitioners, and to secure funding and publication opportunities. It ensures that the study contributes to the ongoing discourse and development of mass communications as a discipline.

Strategies for Ensuring Relevance:

• Conduct a thorough review of current literature to identify gaps, emerging trends, or unresolved questions.
• Align research questions and hypotheses with theoretical frameworks or pressing societal issues.
• Consider the practical implications and potential impact of the research on the field.

Researchability and Empirical Testing Potential

Definition: Researchability refers to the feasibility of addressing the research questions and testing the hypotheses through empirical methods. This includes the availability of data, appropriateness of methodology, and the potential for gathering evidence to support or refute the hypotheses.

Importance: For research to contribute to the body of knowledge, it must be capable of being rigorously investigated using empirical methods. Research questions and hypotheses with high empirical testing potential allow for the derivation of meaningful, verifiable insights.

Strategies for Enhancing Researchability:

• Ensure that the variables involved can be accurately measured or observed using existing tools or methods.
• Design hypotheses that are testable within the constraints of time, resources, and ethical considerations.
• Consider the practical aspects of data collection, including access to participants, media content, or archival resources.

Crafting research questions and hypotheses that are clear and precise, relevant to the field, and amenable to empirical investigation is crucial for conducting impactful research in mass communications. These criteria not only guide the research process but also enhance the study’s validity, reliability, and contribution to the field, fostering a deeper understanding of the complex dynamics that shape media and communication in society.

7.12 Common Mistakes to Avoid in Formulating Research Questions and Hypotheses

When embarking on a research project, especially in a field as dynamic as mass communications, the formulation of research questions and hypotheses is a critical step that sets the stage for the entire study. However, researchers, particularly those new to the field, may encounter pitfalls that can compromise the clarity, relevance, and feasibility of their research. This section highlights common mistakes to avoid in the formulation process, ensuring that research questions and hypotheses are both robust and actionable.

Formulating Questions and Hypotheses That Are Too Broad or Vague

Issue: Broad or vague questions and hypotheses lack specificity and focus, making it difficult to define the scope of the study or determine the appropriate methodology for investigation.

Impact: They can lead to an unwieldy research project with diffuse objectives, posing challenges in data collection, analysis, and interpretation of findings.

Avoidance Strategy: Narrow down the research topic by focusing on specific aspects, populations, or contexts. Use the literature review to identify gaps and refine the research focus to a manageable scope.

Confusing Research Questions with Interview or Survey Questions

Issue: There is a distinction between overarching research questions that guide a study and the specific questions posed in interviews or surveys. Confusing the two can lead to a misalignment between the study’s objectives and the data collection process.

Impact: This confusion can result in collecting data that do not effectively address the research questions, undermining the study’s ability to generate meaningful insights.

Avoidance Strategy: Clearly delineate between the broad research questions that frame your study and the specific items or prompts used in data collection instruments. Ensure that each interview or survey question is directly linked to and serves the purpose of answering the overarching research questions.

Creating Untestable Hypotheses

Issue: Hypotheses that are not empirically testable, either due to the abstract nature of the constructs involved or the lack of available methods for measurement, pose significant challenges to the research process.

Impact: Untestable hypotheses cannot be substantiated or refuted through empirical evidence, limiting the study’s contribution to the field and its scientific merit.

Avoidance Strategy: Ensure that all variables in the hypothesis can be measured or manipulated with existing research methods. Operationalize abstract concepts clearly and consider the feasibility of empirical testing during the hypothesis formulation stage.

7.13 Best Practices for Robust Formulation

Alignment with Theoretical Frameworks: Ground your research questions and hypotheses within established theories or models in mass communications, ensuring they contribute to the broader academic dialogue.

Consultation with Peers and Mentors: Engage in discussions with peers, mentors, or experts in the field to refine your research questions and hypotheses, leveraging their insights to avoid common pitfalls.

Pilot Testing: Consider conducting a pilot study or preliminary analysis to test the feasibility of your research questions and hypotheses, allowing for adjustments before the full-scale study.

By avoiding these common mistakes and adhering to best practices, researchers can formulate research questions and hypotheses that are clear, focused, and empirically testable. This careful preparation enhances the quality and impact of research in mass communications, contributing valuable insights into the complex interplay between media, technology, and society.

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• Formulation of Hypothesis

Children who spend more time playing outside are more likely to be imaginative. What do you think this statement is an example of in terms of scientific research ? If you guessed a hypothesis, then you'd be correct. The formulation of hypotheses is a fundamental step in psychology research.

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What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV, and states how it will influence the DV. 

Which type of hypothesis is also known as a two-tailed hypothesis? 

What type of hypothesis matches the following definition. A predictive statement that researchers use when it is thought that the IV will not influence the DV.

What type of hypothesis is the following example. There will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

Is the following example a falsifiable hypothesis, "leprechauns always find the pot of gold at the end of the rainbow".

What type of hypothesis is the following example. There will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.

Is memory an operationalised variable that could be used in a good hypothesis? 

What type of hypothesis is the following example. People with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.  

What type of hypothesis matches the following definition. A hypothesis that states that the IV will influence the DV. But, the hypothesis does not state how the IV will influence the DV. 

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• First, we will discuss the importance of hypotheses in research.
• We will then cover formulating hypotheses in research, including the steps in the formulation of hypotheses in research methodology.
• We will provide examples of hypotheses in research throughout the explanation.
• Finally, we will delve into the different types of hypotheses in research.

What is a Hypothesis?

The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research . To be classed as scientific research , it must be observable, valid, reliable and follow a standardised procedure.

One of the important steps in scientific research is to formulate a hypothesis before starting the study procedure.

The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find.

The hypothesis provides a summary of what direction, if any, is taken to investigate a theory.

In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.

If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.

Importance of Hypothesis in Research

The purpose of including hypotheses in psychology research is:

• To provide a summary of the research, how it will be investigated, and what is expected to be found.
• To provide an answer to the research question.

When carrying out research, researchers first investigate the research area they are interested in. From this, researchers are required to identify a gap in the literature.

Filling the gap essentially means finding what previous work has not been explained yet, investigated to a sufficient degree, or simply expanding or further investigating a theory if doubt exists.

The researcher then forms a research question that the researcher will attempt to answer in their study.

Remember, the hypothesis is a predictive statement of what is expected to happen when testing the research question.

The hypothesis can be used for later data analysis. This includes inferential tests such as hypothesis testing and identifying if statistical findings are significant.

Steps in the Formulation of Hypothesis in Research Methodology

Researchers must follow certain steps to formulate testable hypotheses when conducting research.

Overall, the researcher has to consider the direction of the research, i.e. will it be looking for a difference caused by independent variables ? Or will it be more concerned with the correlation between variables?

All researchers will likely complete the following.

• Investigating background research in the area of interest.
• Formulating or investigating a theory.
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works.

The above steps are used to formulate testable hypotheses.

The Formulation of Testable Hypotheses

The hypothesis is important in research as it indicates what and how a variable will be investigated.

The hypothesis essentially summarises what and how something will be investigated. This is important as it ensures that the researcher has carefully planned how the research will be done, as the researchers have to follow a set procedure to conduct research.

This is known as the scientific method.

Formulating Hypotheses in Research

When formulating hypotheses, things that researchers should consider are:

Types of Hypotheses in Research

Researchers can propose different types of hypotheses when carrying out research.

The following research scenario will be discussed to show examples of each type of hypothesis that the researchers could use. "A research team was investigating whether memory performance is affected by depression ."

The identified independent variable is the severity of depression scores, and the dependent variable is the scores from a memory performance task.

The null hypothesis predicts that the results will show no or little effect. The null hypothesis is a predictive statement that researchers use when it is thought that the IV will not influence the DV.

In this case, the null hypothesis would be there will be no difference in memory scores on the MMSE test of those who are diagnosed with depression and those who are not.

An alternative hypothesis is a predictive statement used when it is thought that the IV will influence the DV. The alternative hypothesis is also called a non-directional, two-tailed hypothesis, as it predicts the results can go either way, e.g. increase or decrease.

The example in this scenario is there will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.

The directional alternative hypothesis states how the IV will influence the DV, identifying a specific direction, such as if there will be an increase or decrease in the observed results.

The example in this scenario is people with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.

Example Hypothesis in Research

To summarise, let's look at an example of a straightforward hypothesis that indicates the relationship between two variables: the independent and the dependent.

If you stay up late, you will feel tired the following day; the more caffeine you drink, the harder you find it to fall asleep, or the more sunlight plants get, the taller they will grow.

Formulation of Hypothesis - Key Takeaways

• The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research. One of the important steps in scientific research is to create a hypothesis.
• The hypothesis is a predictive, testable statement concerning the outcome/results that the researcher expects to find.
• Hypotheses are needed in research to provide a summary of what the research is, how to investigate a theory and what is expected to be found, and to provide an answer to the research question so that the hypothesis can be used for later data analysis.
• There are requirements for the formulation of testable hypotheses. The hypotheses should identify and operationalise the IV and DV. In addition, they should describe the nature of the relationship between the IV and DV.
• There are different types of hypotheses: Null hypothesis, Alternative hypothesis (this is also known as the non-directional, two-tailed hypothesis), and Directional hypothesis (this is also known as the one-tailed hypothesis).

Flashcards in Formulation of Hypothesis 9

Directional, alternative hypothesis 

Alternative hypothesis 

Null hypothesis 

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Frequently Asked Questions about Formulation of Hypothesis

What are the 3 types of hypotheses?

The three types of hypotheses are:

• Null hypothesis 
• Alternative hypothesis 
• Directional/non-directional hypothesis 

What is an example of a hypothesis in psychology?

An example of a null hypothesis in psychology is, there will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

What are the steps in formulating a hypothesis?

All researchers will likely complete the following

• Investigating background research in the area of interest 
• Formulating or investigating a theory 
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works 

What is formulation of hypothesis in research? 

The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research question based on background research.

How to formulate  null and alternative hypothesis?

When formulating a null hypothesis the researcher would state a prediction that they expect to see no difference in the dependent variable when the independent variable changes or is manipulated. Whereas, when using an alternative hypothesis then it would be predicted that there will be a change in the dependent variable. The researcher can state in which direction they expect the results to go. 

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Research Process Steps: What they are + How To Follow

There are various approaches to conducting basic and applied research. This article explains the research process steps you should know. Whether you are doing basic research or applied research, there are many ways of doing it. In some ways, each research study is unique since it is conducted at a different time and place.

Conducting research might be difficult, but there are clear processes to follow. The research process starts with a broad idea for a topic. This article will assist you through the research process steps, helping you focus and develop your topic.

Research Process Steps

The research process consists of a series of systematic procedures that a researcher must go through in order to generate knowledge that will be considered valuable by the project and focus on the relevant topic.

To conduct effective research, you must understand the research process steps and follow them. Here are a few steps in the research process to make it easier for you:

Step 1: Identify the Problem

Finding an issue or formulating a research question is the first step. A well-defined research problem will guide the researcher through all stages of the research process, from setting objectives to choosing a technique. There are a number of approaches to get insight into a topic and gain a better understanding of it. Such as:

• A preliminary survey
• Case studies
• Interviews with a small group of people
• Observational survey

Step 2: Evaluate the Literature

A thorough examination of the relevant studies is essential to the research process . It enables the researcher to identify the precise aspects of the problem. Once a problem has been found, the investigator or researcher needs to find out more about it.

This stage gives problem-zone background. It teaches the investigator about previous research, how they were conducted, and its conclusions. The researcher can build consistency between his work and others through a literature review. Such a review exposes the researcher to a more significant body of knowledge and helps him follow the research process efficiently.

Step 3: Create Hypotheses

Formulating an original hypothesis is the next logical step after narrowing down the research topic and defining it. A belief solves logical relationships between variables. In order to establish a hypothesis, a researcher must have a certain amount of expertise in the field. 

It is important for researchers to keep in mind while formulating a hypothesis that it must be based on the research topic. Researchers are able to concentrate their efforts and stay committed to their objectives when they develop theories to guide their work.

Step 4: The Research Design

Research design is the plan for achieving objectives and answering research questions. It outlines how to get the relevant information. Its goal is to design research to test hypotheses, address the research questions, and provide decision-making insights.

The research design aims to minimize the time, money, and effort required to acquire meaningful evidence. This plan fits into four categories:

• Exploration and Surveys
• Data Analysis
• Observation

Step 5: Describe Population

Research projects usually look at a specific group of people, facilities, or how technology is used in the business. In research, the term population refers to this study group. The research topic and purpose help determine the study group.

Suppose a researcher wishes to investigate a certain group of people in the community. In that case, the research could target a specific age group, males or females, a geographic location, or an ethnic group. A final step in a study’s design is to specify its sample or population so that the results may be generalized.

Step 6: Data Collection

Data collection is important in obtaining the knowledge or information required to answer the research issue. Every research collected data, either from the literature or the people being studied. Data must be collected from the two categories of researchers. These sources may provide primary data.

• Questionnaire

Secondary data categories are:

• Literature survey
• Official, unofficial reports
• An approach based on library resources

Step 7: Data Analysis

During research design, the researcher plans data analysis. After collecting data, the researcher analyzes it. The data is examined based on the approach in this step. The research findings are reviewed and reported.

Data analysis involves a number of closely related stages, such as setting up categories, applying these categories to raw data through coding and tabulation, and then drawing statistical conclusions. The researcher can examine the acquired data using a variety of statistical methods.

Step 8: The Report-writing

After completing these steps, the researcher must prepare a report detailing his findings. The report must be carefully composed with the following in mind:

• The Layout: On the first page, the title, date, acknowledgments, and preface should be on the report. A table of contents should be followed by a list of tables, graphs, and charts if any.
• Introduction: It should state the research’s purpose and methods. This section should include the study’s scope and limits.
• Summary of Findings: A non-technical summary of findings and recommendations will follow the introduction. The findings should be summarized if they’re lengthy.
• Principal Report: The main body of the report should make sense and be broken up into sections that are easy to understand.
• Conclusion: The researcher should restate his findings at the end of the main text. It’s the final result.

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The research process involves several steps that make it easy to complete the research successfully. The steps in the research process described above depend on each other, and the order must be kept. So, if we want to do a research project, we should follow the research process steps.

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Scientific Method Steps in Psychology Research

Steps, Uses, and Key Terms

Verywell / Theresa Chiechi

How do researchers investigate psychological phenomena? They utilize a process known as the scientific method to study different aspects of how people think and behave.

When conducting research, the scientific method steps to follow are:

• Observe what you want to investigate
• Ask a research question and make predictions
• Test the hypothesis and collect data
• Examine the results and draw conclusions
• Report and share the results 

This process not only allows scientists to investigate and understand different psychological phenomena but also provides researchers and others a way to share and discuss the results of their studies.

Generally, there are five main steps in the scientific method, although some may break down this process into six or seven steps. An additional step in the process can also include developing new research questions based on your findings.

What Is the Scientific Method?

What is the scientific method and how is it used in psychology?

The scientific method consists of five steps. It is essentially a step-by-step process that researchers can follow to determine if there is some type of relationship between two or more variables.

By knowing the steps of the scientific method, you can better understand the process researchers go through to arrive at conclusions about human behavior.

Scientific Method Steps

While research studies can vary, these are the basic steps that psychologists and scientists use when investigating human behavior.

The following are the scientific method steps:

Step 1. Make an Observation

Before a researcher can begin, they must choose a topic to study. Once an area of interest has been chosen, the researchers must then conduct a thorough review of the existing literature on the subject. This review will provide valuable information about what has already been learned about the topic and what questions remain to be answered.

A literature review might involve looking at a considerable amount of written material from both books and academic journals dating back decades.

The relevant information collected by the researcher will be presented in the introduction section of the final published study results. This background material will also help the researcher with the first major step in conducting a psychology study: formulating a hypothesis.

Step 2. Ask a Question

Once a researcher has observed something and gained some background information on the topic, the next step is to ask a question. The researcher will form a hypothesis, which is an educated guess about the relationship between two or more variables

For example, a researcher might ask a question about the relationship between sleep and academic performance: Do students who get more sleep perform better on tests at school?

In order to formulate a good hypothesis, it is important to think about different questions you might have about a particular topic.

You should also consider how you could investigate the causes. Falsifiability is an important part of any valid hypothesis. In other words, if a hypothesis was false, there needs to be a way for scientists to demonstrate that it is false.

Step 3. Test Your Hypothesis and Collect Data

Once you have a solid hypothesis, the next step of the scientific method is to put this hunch to the test by collecting data. The exact methods used to investigate a hypothesis depend on exactly what is being studied. There are two basic forms of research that a psychologist might utilize: descriptive research or experimental research.

Descriptive research is typically used when it would be difficult or even impossible to manipulate the variables in question. Examples of descriptive research include case studies, naturalistic observation , and correlation studies. Phone surveys that are often used by marketers are one example of descriptive research.

Correlational studies are quite common in psychology research. While they do not allow researchers to determine cause-and-effect, they do make it possible to spot relationships between different variables and to measure the strength of those relationships. 

Experimental research is used to explore cause-and-effect relationships between two or more variables. This type of research involves systematically manipulating an independent variable and then measuring the effect that it has on a defined dependent variable .

One of the major advantages of this method is that it allows researchers to actually determine if changes in one variable actually cause changes in another.

While psychology experiments are often quite complex, a simple experiment is fairly basic but does allow researchers to determine cause-and-effect relationships between variables. Most simple experiments use a control group (those who do not receive the treatment) and an experimental group (those who do receive the treatment).

Step 4. Examine the Results and Draw Conclusions

Once a researcher has designed the study and collected the data, it is time to examine this information and draw conclusions about what has been found.  Using statistics , researchers can summarize the data, analyze the results, and draw conclusions based on this evidence.

So how does a researcher decide what the results of a study mean? Not only can statistical analysis support (or refute) the researcher’s hypothesis; it can also be used to determine if the findings are statistically significant.

When results are said to be statistically significant, it means that it is unlikely that these results are due to chance.

Based on these observations, researchers must then determine what the results mean. In some cases, an experiment will support a hypothesis, but in other cases, it will fail to support the hypothesis.

So what happens if the results of a psychology experiment do not support the researcher's hypothesis? Does this mean that the study was worthless?

Just because the findings fail to support the hypothesis does not mean that the research is not useful or informative. In fact, such research plays an important role in helping scientists develop new questions and hypotheses to explore in the future.

After conclusions have been drawn, the next step is to share the results with the rest of the scientific community. This is an important part of the process because it contributes to the overall knowledge base and can help other scientists find new research avenues to explore.

Step 5. Report the Results

The final step in a psychology study is to report the findings. This is often done by writing up a description of the study and publishing the article in an academic or professional journal. The results of psychological studies can be seen in peer-reviewed journals such as  Psychological Bulletin , the  Journal of Social Psychology ,  Developmental Psychology , and many others.

The structure of a journal article follows a specified format that has been outlined by the  American Psychological Association (APA) . In these articles, researchers:

• Provide a brief history and background on previous research
• Present their hypothesis
• Identify who participated in the study and how they were selected
• Provide operational definitions for each variable
• Describe the measures and procedures that were used to collect data
• Explain how the information collected was analyzed
• Discuss what the results mean

Why is such a detailed record of a psychological study so important? By clearly explaining the steps and procedures used throughout the study, other researchers can then replicate the results. The editorial process employed by academic and professional journals ensures that each article that is submitted undergoes a thorough peer review, which helps ensure that the study is scientifically sound.

Once published, the study becomes another piece of the existing puzzle of our knowledge base on that topic.

Before you begin exploring the scientific method steps, here's a review of some key terms and definitions that you should be familiar with:

• Falsifiable : The variables can be measured so that if a hypothesis is false, it can be proven false
• Hypothesis : An educated guess about the possible relationship between two or more variables
• Variable : A factor or element that can change in observable and measurable ways
• Operational definition : A full description of exactly how variables are defined, how they will be manipulated, and how they will be measured

Uses for the Scientific Method

The  goals of psychological studies  are to describe, explain, predict and perhaps influence mental processes or behaviors. In order to do this, psychologists utilize the scientific method to conduct psychological research. The scientific method is a set of principles and procedures that are used by researchers to develop questions, collect data, and reach conclusions.

Goals of Scientific Research in Psychology

Researchers seek not only to describe behaviors and explain why these behaviors occur; they also strive to create research that can be used to predict and even change human behavior.

Psychologists and other social scientists regularly propose explanations for human behavior. On a more informal level, people make judgments about the intentions, motivations , and actions of others on a daily basis.

While the everyday judgments we make about human behavior are subjective and anecdotal, researchers use the scientific method to study psychology in an objective and systematic way. The results of these studies are often reported in popular media, which leads many to wonder just how or why researchers arrived at the conclusions they did.

Examples of the Scientific Method

Now that you're familiar with the scientific method steps, it's useful to see how each step could work with a real-life example.

Say, for instance, that researchers set out to discover what the relationship is between psychotherapy and anxiety .

• Step 1. Make an observation : The researchers choose to focus their study on adults ages 25 to 40 with generalized anxiety disorder.
• Step 2. Ask a question : The question they want to answer in their study is: Do weekly psychotherapy sessions reduce symptoms in adults ages 25 to 40 with generalized anxiety disorder?
• Step 3. Test your hypothesis : Researchers collect data on participants' anxiety symptoms . They work with therapists to create a consistent program that all participants undergo. Group 1 may attend therapy once per week, whereas group 2 does not attend therapy.
• Step 4. Examine the results : Participants record their symptoms and any changes over a period of three months. After this period, people in group 1 report significant improvements in their anxiety symptoms, whereas those in group 2 report no significant changes.
• Step 5. Report the results : Researchers write a report that includes their hypothesis, information on participants, variables, procedure, and conclusions drawn from the study. In this case, they say that "Weekly therapy sessions are shown to reduce anxiety symptoms in adults ages 25 to 40."

Of course, there are many details that go into planning and executing a study such as this. But this general outline gives you an idea of how an idea is formulated and tested, and how researchers arrive at results using the scientific method.

Erol A. How to conduct scientific research ? Noro Psikiyatr Ars . 2017;54(2):97-98. doi:10.5152/npa.2017.0120102

University of Minnesota. Psychologists use the scientific method to guide their research .

Shaughnessy, JJ, Zechmeister, EB, & Zechmeister, JS. Research Methods In Psychology . New York: McGraw Hill Education; 2015.

By Kendra Cherry, MSEd Kendra Cherry, MS, is a psychosocial rehabilitation specialist, psychology educator, and author of the "Everything Psychology Book."

Formulating Research Hypothesis and Objective

• First Online: 01 March 2024

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• Animesh Hazari 2  

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Formulating a research hypothesis and objectives is the first and foremost step in any research process as they provide a clear direction and purpose for your study. In this chapter, we shall learn about formulating an ideal research hypothesis and objectives. Formulation and development of the hypothesis and objectives take place under the following key steps:

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Hazari, A. (2023). Formulating Research Hypothesis and Objective. In: Research Methodology for Allied Health Professionals. Springer, Singapore. https://doi.org/10.1007/978-981-99-8925-6_4

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FORMULATING AND TESTING HYPOTHESIS

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What is a Hypothesis?

The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research . To be classed as scientific research , it must be observable, valid, reliable and follow a standardised procedure.

One of the important steps in scientific research is to formulate a hypothesis before starting the study procedure.

The hypothesis is a predictive, testable statement predicting the outcome and the results the researcher expects to find.

The hypothesis provides a summary of what direction, if any, is taken to investigate a theory.

In scientific research, there is a criterion that hypotheses need to be met to be regarded as acceptable.

If a hypothesis is disregarded, the research may be rejected by the community of psychology researchers.

Importance of Hypothesis in Research

The purpose of including hypotheses in psychology research is:

• To provide a summary of the research, how it will be investigated, and what is expected to be found.
• To provide an answer to the research question.

When carrying out research, researchers first investigate the research area they are interested in. From this, researchers are required to identify a gap in the literature.

Filling the gap essentially means finding what previous work has not been explained yet, investigated to a sufficient degree, or simply expanding or further investigating a theory if doubt exists.

The researcher then forms a research question that the researcher will attempt to answer in their study.

Remember, the hypothesis is a predictive statement of what is expected to happen when testing the research question.

The hypothesis can be used for later data analysis. This includes inferential tests such as hypothesis testing and identifying if statistical findings are significant.

Steps in the Formulation of Hypothesis in Research Methodology

Researchers must follow certain steps to formulate testable hypotheses when conducting research.

Overall, the researcher has to consider the direction of the research, i.e. will it be looking for a difference caused by independent variables ? Or will it be more concerned with the correlation between variables?

All researchers will likely complete the following.

• Investigating background research in the area of interest.
• Formulating or investigating a theory.
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works.

The above steps are used to formulate testable hypotheses.

The Formulation of Testable Hypotheses

The hypothesis is important in research as it indicates what and how a variable will be investigated.

The hypothesis essentially summarises what and how something will be investigated. This is important as it ensures that the researcher has carefully planned how the research will be done, as the researchers have to follow a set procedure to conduct research.

This is known as the scientific method.

Formulating Hypotheses in Research

When formulating hypotheses, things that researchers should consider are:

Types of Hypotheses in Research

Researchers can propose different types of hypotheses when carrying out research.

The following research scenario will be discussed to show examples of each type of hypothesis that the researchers could use. "A research team was investigating whether memory performance is affected by depression ."

The identified independent variable is the severity of depression scores, and the dependent variable is the scores from a memory performance task.

The null hypothesis predicts that the results will show no or little effect. The null hypothesis is a predictive statement that researchers use when it is thought that the IV will not influence the DV.

In this case, the null hypothesis would be there will be no difference in memory scores on the MMSE test of those who are diagnosed with depression and those who are not.

An alternative hypothesis is a predictive statement used when it is thought that the IV will influence the DV. The alternative hypothesis is also called a non-directional, two-tailed hypothesis, as it predicts the results can go either way, e.g. increase or decrease.

The example in this scenario is there will be an observed difference in scores from a memory performance task between people with high- or low-depressive scores.

The directional alternative hypothesis states how the IV will influence the DV, identifying a specific direction, such as if there will be an increase or decrease in the observed results.

The example in this scenario is people with low depressive scores will perform better in the memory performance task than people who score higher in depressive symptoms.

Example Hypothesis in Research

To summarise, let's look at an example of a straightforward hypothesis that indicates the relationship between two variables: the independent and the dependent.

If you stay up late, you will feel tired the following day; the more caffeine you drink, the harder you find it to fall asleep, or the more sunlight plants get, the taller they will grow.

Formulation of Hypothesis - Key Takeaways

• The current community of psychologists believe that the best approach to understanding behaviour is to conduct scientific research. One of the important steps in scientific research is to create a hypothesis.
• The hypothesis is a predictive, testable statement concerning the outcome/results that the researcher expects to find.
• Hypotheses are needed in research to provide a summary of what the research is, how to investigate a theory and what is expected to be found, and to provide an answer to the research question so that the hypothesis can be used for later data analysis.
• There are requirements for the formulation of testable hypotheses. The hypotheses should identify and operationalise the IV and DV. In addition, they should describe the nature of the relationship between the IV and DV.
• There are different types of hypotheses: Null hypothesis, Alternative hypothesis (this is also known as the non-directional, two-tailed hypothesis), and Directional hypothesis (this is also known as the one-tailed hypothesis).

Flashcards in Formulation of Hypothesis 9

Directional, alternative hypothesis 

Alternative hypothesis 

Null hypothesis 

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Frequently Asked Questions about Formulation of Hypothesis

What are the 3 types of hypotheses?

The three types of hypotheses are:

• Null hypothesis 
• Alternative hypothesis 
• Directional/non-directional hypothesis 

What is an example of a hypothesis in psychology?

An example of a null hypothesis in psychology is, there will be no observed difference in scores from a memory performance task between people with high- or low-depressive scores.

What are the steps in formulating a hypothesis?

All researchers will likely complete the following

• Investigating background research in the area of interest 
• Formulating or investigating a theory 
• Identify how the theory will be tested and what the researcher expects to find based on relevant, previously published scientific works 

What is formulation of hypothesis in research? 

The formulation of a hypothesis in research is when the researcher formulates a predictive statement of what is expected to happen when testing the research question based on background research.

How to formulate  null and alternative hypothesis?

When formulating a null hypothesis the researcher would state a prediction that they expect to see no difference in the dependent variable when the independent variable changes or is manipulated. Whereas, when using an alternative hypothesis then it would be predicted that there will be a change in the dependent variable. The researcher can state in which direction they expect the results to go. 

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Pharmacology Unit, Faculty of Pharmacy, AIMST University, Semeling, 08100 Bedong. Kedah Darul Aman, Malaysia

Mohammed Naseeruddin Inamdar

1 Department of Pharmacology, Al-Ameen College of Pharmacy, Bengaluru, Karnataka, India

Gowraganahalli Jagadeesh

2 Division of Cardiovascular and Renal Products, Center for Drug Evaluation and Research, US Food and Drug Administration, Silver Spring, USA

An interactive workshop on ‘The Critical Steps for Successful Research: The Research Proposal and Scientific Writing’ was conducted in conjunction with the 64 th Annual Conference of the Indian Pharmaceutical Congress-2012 at Chennai, India. In essence, research is performed to enlighten our understanding of a contemporary issue relevant to the needs of society. To accomplish this, a researcher begins search for a novel topic based on purpose, creativity, critical thinking, and logic. This leads to the fundamental pieces of the research endeavor: Question, objective, hypothesis, experimental tools to test the hypothesis, methodology, and data analysis. When correctly performed, research should produce new knowledge. The four cornerstones of good research are the well-formulated protocol or proposal that is well executed, analyzed, discussed and concluded. This recent workshop educated researchers in the critical steps involved in the development of a scientific idea to its successful execution and eventual publication.

INTRODUCTION

Creativity and critical thinking are of particular importance in scientific research. Basically, research is original investigation undertaken to gain knowledge and understand concepts in major subject areas of specialization, and includes the generation of ideas and information leading to new or substantially improved scientific insights with relevance to the needs of society. Hence, the primary objective of research is to produce new knowledge. Research is both theoretical and empirical. It is theoretical because the starting point of scientific research is the conceptualization of a research topic and development of a research question and hypothesis. Research is empirical (practical) because all of the planned studies involve a series of observations, measurements, and analyses of data that are all based on proper experimental design.[ 1 – 9 ]

The subject of this report is to inform readers of the proceedings from a recent workshop organized by the 64 th Annual conference of the ‘ Indian Pharmaceutical Congress ’ at SRM University, Chennai, India, from 05 to 06 December 2012. The objectives of the workshop titled ‘The Critical Steps for Successful Research: The Research Proposal and Scientific Writing,’ were to assist participants in developing a strong fundamental understanding of how best to develop a research or study protocol, and communicate those research findings in a conference setting or scientific journal. Completing any research project requires meticulous planning, experimental design and execution, and compilation and publication of findings in the form of a research paper. All of these are often unfamiliar to naïve researchers; thus, the purpose of this workshop was to teach participants to master the critical steps involved in the development of an idea to its execution and eventual publication of the results (See the last section for a list of learning objectives).

THE STRUCTURE OF THE WORKSHOP

The two-day workshop was formatted to include key lectures and interactive breakout sessions that focused on protocol development in six subject areas of the pharmaceutical sciences. This was followed by sessions on scientific writing. DAY 1 taught the basic concepts of scientific research, including: (1) how to formulate a topic for research and to describe the what, why , and how of the protocol, (2) biomedical literature search and review, (3) study designs, statistical concepts, and result analyses, and (4) publication ethics. DAY 2 educated the attendees on the basic elements and logistics of writing a scientific paper and thesis, and preparation of poster as well as oral presentations.

The final phase of the workshop was the ‘Panel Discussion,’ including ‘Feedback/Comments’ by participants. There were thirteen distinguished speakers from India and abroad. Approximately 120 post-graduate and pre-doctoral students, young faculty members, and scientists representing industries attended the workshop from different parts of the country. All participants received a printed copy of the workshop manual and supporting materials on statistical analyses of data.

THE BASIC CONCEPTS OF RESEARCH: THE KEY TO GETTING STARTED IN RESEARCH

A research project generally comprises four key components: (1) writing a protocol, (2) performing experiments, (3) tabulating and analyzing data, and (4) writing a thesis or manuscript for publication.

Fundamentals in the research process

A protocol, whether experimental or clinical, serves as a navigator that evolves from a basic outline of the study plan to become a qualified research or grant proposal. It provides the structural support for the research. Dr. G. Jagadeesh (US FDA), the first speaker of the session, spoke on ‘ Fundamentals in research process and cornerstones of a research project .’ He discussed at length the developmental and structural processes in preparing a research protocol. A systematic and step-by-step approach is necessary in planning a study. Without a well-designed protocol, there would be a little chance for successful completion of a research project or an experiment.

Research topic

The first and the foremost difficult task in research is to identify a topic for investigation. The research topic is the keystone of the entire scientific enterprise. It begins the project, drives the entire study, and is crucial for moving the project forward. It dictates the remaining elements of the study [ Table 1 ] and thus, it should not be too narrow or too broad or unfocused. Because of these potential pitfalls, it is essential that a good or novel scientific idea be based on a sound concept. Creativity, critical thinking, and logic are required to generate new concepts and ideas in solving a research problem. Creativity involves critical thinking and is associated with generating many ideas. Critical thinking is analytical, judgmental, and involves evaluating choices before making a decision.[ 4 ] Thus, critical thinking is convergent type thinking that narrows and refines those divergent ideas and finally settles to one idea for an in-depth study. The idea on which a research project is built should be novel, appropriate to achieve within the existing conditions, and useful to the society at large. Therefore, creativity and critical thinking assist biomedical scientists in research that results in funding support, novel discovery, and publication.[ 1 , 4 ]

Elements of a study protocol

Research question

The next most crucial aspect of a study protocol is identifying a research question. It should be a thought-provoking question. The question sets the framework. It emerges from the title, findings/results, and problems observed in previous studies. Thus, mastering the literature, attendance at conferences, and discussion in journal clubs/seminars are sources for developing research questions. Consider the following example in developing related research questions from the research topic.

Hepatoprotective activity of Terminalia arjuna and Apium graveolens on paracetamol-induced liver damage in albino rats.

How is paracetamol metabolized in the body? Does it involve P450 enzymes? How does paracetamol cause liver injury? What are the mechanisms by which drugs can alleviate liver damage? What biochemical parameters are indicative of liver injury? What major endogenous inflammatory molecules are involved in paracetamol-induced liver damage?

A research question is broken down into more precise objectives. The objectives lead to more precise methods and definition of key terms. The objectives should be SMART-Specific, Measurable, Achievable, Realistic, Time-framed,[ 10 ] and should cover the entire breadth of the project. The objectives are sometimes organized into hierarchies: Primary, secondary, and exploratory; or simply general and specific. Study the following example:

To evaluate the safety and tolerability of single oral doses of compound X in normal volunteers.

To assess the pharmacokinetic profile of compound X following single oral doses.

To evaluate the incidence of peripheral edema reported as an adverse event.

The objectives and research questions are then formulated into a workable or testable hypothesis. The latter forces us to think carefully about what comparisons will be needed to answer the research question, and establishes the format for applying statistical tests to interpret the results. The hypothesis should link a process to an existing or postulated biologic pathway. A hypothesis is written in a form that can yield measurable results. Studies that utilize statistics to compare groups of data should have a hypothesis. Consider the following example:

• The hepatoprotective activity of Terminalia arjuna is superior to that of Apium graveolens against paracetamol-induced liver damage in albino rats.

All biological research, including discovery science, is hypothesis-driven. However, not all studies need be conducted with a hypothesis. For example, descriptive studies (e.g., describing characteristics of a plant, or a chemical compound) do not need a hypothesis.[ 1 ]

Relevance of the study

Another important section to be included in the protocol is ‘significance of the study.’ Its purpose is to justify the need for the research that is being proposed (e.g., development of a vaccine for a disease). In summary, the proposed study should demonstrate that it represents an advancement in understanding and that the eventual results will be meaningful, contribute to the field, and possibly even impact society.

Biomedical literature

A literature search may be defined as the process of examining published sources of information on a research or review topic, thesis, grant application, chemical, drug, disease, or clinical trial, etc. The quantity of information available in print or electronically (e.g., the internet) is immense and growing with time. A researcher should be familiar with the right kinds of databases and search engines to extract the needed information.[ 3 , 6 ]

Dr. P. Balakumar (Institute of Pharmacy, Rajendra Institute of Technology and Sciences, Sirsa, Haryana; currently, Faculty of Pharmacy, AIMST University, Malaysia) spoke on ‘ Biomedical literature: Searching, reviewing and referencing .’ He schematically explained the basis of scientific literature, designing a literature review, and searching literature. After an introduction to the genesis and diverse sources of scientific literature searches, the use of PubMed, one of the premier databases used for biomedical literature searches world-wide, was illustrated with examples and screenshots. Several companion databases and search engines are also used for finding information related to health sciences, and they include Embase, Web of Science, SciFinder, The Cochrane Library, International Pharmaceutical Abstracts, Scopus, and Google Scholar.[ 3 ] Literature searches using alternative interfaces for PubMed such as GoPubMed, Quertle, PubFocus, Pubget, and BibliMed were discussed. The participants were additionally informed of databases on chemistry, drugs and drug targets, clinical trials, toxicology, and laboratory animals (reviewed in ref[ 3 ]).

Referencing and bibliography are essential in scientific writing and publication.[ 7 ] Referencing systems are broadly classified into two major types, such as Parenthetical and Notation systems. Parenthetical referencing is also known as Harvard style of referencing, while Vancouver referencing style and ‘Footnote’ or ‘Endnote’ are placed under Notation referencing systems. The participants were educated on each referencing system with examples.

Bibliography management

Dr. Raj Rajasekaran (University of California at San Diego, CA, USA) enlightened the audience on ‘ bibliography management ’ using reference management software programs such as Reference Manager ® , Endnote ® , and Zotero ® for creating and formatting bibliographies while writing a manuscript for publication. The discussion focused on the use of bibliography management software in avoiding common mistakes such as incomplete references. Important steps in bibliography management, such as creating reference libraries/databases, searching for references using PubMed/Google scholar, selecting and transferring selected references into a library, inserting citations into a research article and formatting bibliographies, were presented. A demonstration of Zotero®, a freely available reference management program, included the salient features of the software, adding references from PubMed using PubMed ID, inserting citations and formatting using different styles.

Writing experimental protocols

The workshop systematically instructed the participants in writing ‘ experimental protocols ’ in six disciplines of Pharmaceutical Sciences.: (1) Pharmaceutical Chemistry (presented by Dr. P. V. Bharatam, NIPER, Mohali, Punjab); (2) Pharmacology (presented by Dr. G. Jagadeesh and Dr. P. Balakumar); (3) Pharmaceutics (presented by Dr. Jayant Khandare, Piramal Life Sciences, Mumbai); (4) Pharmacy Practice (presented by Dr. Shobha Hiremath, Al-Ameen College of Pharmacy, Bengaluru); (5) Pharmacognosy and Phytochemistry (presented by Dr. Salma Khanam, Al-Ameen College of Pharmacy, Bengaluru); and (6) Pharmaceutical Analysis (presented by Dr. Saranjit Singh, NIPER, Mohali, Punjab). The purpose of the research plan is to describe the what (Specific Aims/Objectives), why (Background and Significance), and how (Design and Methods) of the proposal.

The research plan should answer the following questions: (a) what do you intend to do; (b) what has already been done in general, and what have other researchers done in the field; (c) why is this worth doing; (d) how is it innovative; (e) what will this new work add to existing knowledge; and (f) how will the research be accomplished?

In general, the format used by the faculty in all subjects is shown in Table 2 .

Elements of a research protocol

Biostatistics

Biostatistics is a key component of biomedical research. Highly reputed journals like The Lancet, BMJ, Journal of the American Medical Association, and many other biomedical journals include biostatisticians on their editorial board or reviewers list. This indicates that a great importance is given for learning and correctly employing appropriate statistical methods in biomedical research. The post-lunch session on day 1 of the workshop was largely committed to discussion on ‘ Basic biostatistics .’ Dr. R. Raveendran (JIPMER, Puducherry) and Dr. Avijit Hazra (PGIMER, Kolkata) reviewed, in parallel sessions, descriptive statistics, probability concepts, sample size calculation, choosing a statistical test, confidence intervals, hypothesis testing and ‘ P ’ values, parametric and non-parametric statistical tests, including analysis of variance (ANOVA), t tests, Chi-square test, type I and type II errors, correlation and regression, and summary statistics. This was followed by a practice and demonstration session. Statistics CD, compiled by Dr. Raveendran, was distributed to the participants before the session began and was demonstrated live. Both speakers worked on a variety of problems that involved both clinical and experimental data. They discussed through examples the experimental designs encountered in a variety of studies and statistical analyses performed for different types of data. For the benefit of readers, we have summarized statistical tests applied frequently for different experimental designs and post-hoc tests [ Figure 1 ].

Conceptual framework for statistical analyses of data. Of the two kinds of variables, qualitative (categorical) and quantitative (numerical), qualitative variables (nominal or ordinal) are not normally distributed. Numerical data that come from normal distributions are analyzed using parametric tests, if not; the data are analyzed using non-parametric tests. The most popularly used Student's t -test compares the means of two populations, data for this test could be paired or unpaired. One-way analysis of variance (ANOVA) is used to compare the means of three or more independent populations that are normally distributed. Applying t test repeatedly in pair (multiple comparison), to compare the means of more than two populations, will increase the probability of type I error (false positive). In this case, for proper interpretation, we need to adjust the P values. Repeated measures ANOVA is used to compare the population means if more than two observations coming from same subject over time. The null hypothesis is rejected with a ‘ P ’ value of less than 0.05, and the difference in population means is considered to be statistically significant. Subsequently, appropriate post-hoc tests are used for pairwise comparisons of population means. Two-way or three-way ANOVA are considered if two (diet, dose) or three (diet, dose, strain) independent factors, respectively, are analyzed in an experiment (not described in the Figure). Categorical nominal unmatched variables (counts or frequencies) are analyzed by Chi-square test (not shown in the Figure)

Research and publication ethics

The legitimate pursuit of scientific creativity is unfortunately being marred by a simultaneous increase in scientific misconduct. A disproportionate share of allegations involves scientists of many countries, and even from respected laboratories. Misconduct destroys faith in science and scientists and creates a hierarchy of fraudsters. Investigating misconduct also steals valuable time and resources. In spite of these facts, most researchers are not aware of publication ethics.

Day 1 of the workshop ended with a presentation on ‘ research and publication ethics ’ by Dr. M. K. Unnikrishnan (College of Pharmaceutical Sciences, Manipal University, Manipal). He spoke on the essentials of publication ethics that included plagiarism (attempting to take credit of the work of others), self-plagiarism (multiple publications by an author on the same content of work with slightly different wordings), falsification (manipulation of research data and processes and omitting critical data or results), gift authorship (guest authorship), ghostwriting (someone other than the named author (s) makes a major contribution), salami publishing (publishing many papers, with minor differences, from the same study), and sabotage (distracting the research works of others to halt their research completion). Additionally, Dr. Unnikrishnan pointed out the ‘ Ingelfinger rule ’ of stipulating that a scientist must not submit the same original research in two different journals. He also advised the audience that authorship is not just credit for the work but also responsibility for scientific contents of a paper. Although some Indian Universities are instituting preventive measures (e.g., use of plagiarism detecting software, Shodhganga digital archiving of doctoral theses), Dr. Unnikrishnan argued for a great need to sensitize young researchers on the nature and implications of scientific misconduct. Finally, he discussed methods on how editors and peer reviewers should ethically conduct themselves while managing a manuscript for publication.

SCIENTIFIC COMMUNICATION: THE KEY TO SUCCESSFUL SELLING OF FINDINGS

Research outcomes are measured through quality publications. Scientists must not only ‘do’ science but must ‘write’ science. The story of the project must be told in a clear, simple language weaving in previous work done in the field, answering the research question, and addressing the hypothesis set forth at the beginning of the study. Scientific publication is an organic process of planning, researching, drafting, revising, and updating the current knowledge for future perspectives. Writing a research paper is no easier than the research itself. The lectures of Day 2 of the workshop dealt with the basic elements and logistics of writing a scientific paper.

An overview of paper structure and thesis writing

Dr. Amitabh Prakash (Adis, Auckland, New Zealand) spoke on ‘ Learning how to write a good scientific paper .’ His presentation described the essential components of an original research paper and thesis (e.g., introduction, methods, results, and discussion [IMRaD]) and provided guidance on the correct order, in which data should appear within these sections. The characteristics of a good abstract and title and the creation of appropriate key words were discussed. Dr. Prakash suggested that the ‘title of a paper’ might perhaps have a chance to make a good impression, and the title might be either indicative (title that gives the purpose of the study) or declarative (title that gives the study conclusion). He also suggested that an abstract is a succinct summary of a research paper, and it should be specific, clear, and concise, and should have IMRaD structure in brief, followed by key words. Selection of appropriate papers to be cited in the reference list was also discussed. Various unethical authorships were enumerated, and ‘The International Committee of Medical Journal Editors (ICMJE) criteria for authorship’ was explained ( http://www.icmje.org/ethical_1author.html ; also see Table 1 in reference #9). The session highlighted the need for transparency in medical publication and provided a clear description of items that needed to be included in the ‘Disclosures’ section (e.g., sources of funding for the study and potential conflicts of interest of all authors, etc.) and ‘Acknowledgements’ section (e.g., writing assistance and input from all individuals who did not meet the authorship criteria). The final part of the presentation was devoted to thesis writing, and Dr. Prakash provided the audience with a list of common mistakes that are frequently encountered when writing a manuscript.

The backbone of a study is description of results through Text, Tables, and Figures. Dr. S. B. Deshpande (Institute of Medical Sciences, Banaras Hindu University, Varanasi, India) spoke on ‘ Effective Presentation of Results .’ The Results section deals with the observations made by the authors and thus, is not hypothetical. This section is subdivided into three segments, that is, descriptive form of the Text, providing numerical data in Tables, and visualizing the observations in Graphs or Figures. All these are arranged in a sequential order to address the question hypothesized in the Introduction. The description in Text provides clear content of the findings highlighting the observations. It should not be the repetition of facts in tables or graphs. Tables are used to summarize or emphasize descriptive content in the text or to present the numerical data that are unrelated. Illustrations should be used when the evidence bearing on the conclusions of a paper cannot be adequately presented in a written description or in a Table. Tables or Figures should relate to each other logically in sequence and should be clear by themselves. Furthermore, the discussion is based entirely on these observations. Additionally, how the results are applied to further research in the field to advance our understanding of research questions was discussed.

Dr. Peush Sahni (All-India Institute of Medical Sciences, New Delhi) spoke on effectively ‘ structuring the Discussion ’ for a research paper. The Discussion section deals with a systematic interpretation of study results within the available knowledge. He said the section should begin with the most important point relating to the subject studied, focusing on key issues, providing link sentences between paragraphs, and ensuring the flow of text. Points were made to avoid history, not repeat all the results, and provide limitations of the study. The strengths and novel findings of the study should be provided in the discussion, and it should open avenues for future research and new questions. The Discussion section should end with a conclusion stating the summary of key findings. Dr. Sahni gave an example from a published paper for writing a Discussion. In another presentation titled ‘ Writing an effective title and the abstract ,’ Dr. Sahni described the important components of a good title, such as, it should be simple, concise, informative, interesting and eye-catching, accurate and specific about the paper's content, and should state the subject in full indicating study design and animal species. Dr. Sahni explained structured (IMRaD) and unstructured abstracts and discussed a few selected examples with the audience.

Language and style in publication

The next lecture of Dr. Amitabh Prakash on ‘ Language and style in scientific writing: Importance of terseness, shortness and clarity in writing ’ focused on the actual sentence construction, language, grammar and punctuation in scientific manuscripts. His presentation emphasized the importance of brevity and clarity in the writing of manuscripts describing biomedical research. Starting with a guide to the appropriate construction of sentences and paragraphs, attendees were given a brief overview of the correct use of punctuation with interactive examples. Dr. Prakash discussed common errors in grammar and proactively sought audience participation in correcting some examples. Additional discussion was centered on discouraging the use of redundant and expendable words, jargon, and the use of adjectives with incomparable words. The session ended with a discussion of words and phrases that are commonly misused (e.g., data vs . datum, affect vs . effect, among vs . between, dose vs . dosage, and efficacy/efficacious vs . effective/effectiveness) in biomedical research manuscripts.

Working with journals

The appropriateness in selecting the journal for submission and acceptance of the manuscript should be determined by the experience of an author. The corresponding author must have a rationale in choosing the appropriate journal, and this depends upon the scope of the study and the quality of work performed. Dr. Amitabh Prakash spoke on ‘ Working with journals: Selecting a journal, cover letter, peer review process and impact factor ’ by instructing the audience in assessing the true value of a journal, understanding principles involved in the peer review processes, providing tips on making an initial approach to the editorial office, and drafting an appropriate cover letter to accompany the submission. His presentation defined the metrics that are most commonly used to measure journal quality (e.g., impact factor™, Eigenfactor™ score, Article Influence™ score, SCOPUS 2-year citation data, SCImago Journal Rank, h-Index, etc.) and guided attendees on the relative advantages and disadvantages of using each metric. Factors to consider when assessing journal quality were discussed, and the audience was educated on the ‘green’ and ‘gold’ open access publication models. Various peer review models (e.g., double-blind, single-blind, non-blind) were described together with the role of the journal editor in assessing manuscripts and selecting suitable reviewers. A typical checklist sent to referees was shared with the attendees, and clear guidance was provided on the best way to address referee feedback. The session concluded with a discussion of the potential drawbacks of the current peer review system.

Poster and oral presentations at conferences

Posters have become an increasingly popular mode of presentation at conferences, as it can accommodate more papers per meeting, has no time constraint, provides a better presenter-audience interaction, and allows one to select and attend papers of interest. In Figure 2 , we provide instructions, design, and layout in preparing a scientific poster. In the final presentation, Dr. Sahni provided the audience with step-by-step instructions on how to write and format posters for layout, content, font size, color, and graphics. Attendees were given specific guidance on the format of text on slides, the use of color, font type and size, and the use of illustrations and multimedia effects. Moreover, the importance of practical tips while delivering oral or poster presentation was provided to the audience, such as speak slowly and clearly, be informative, maintain eye contact, and listen to the questions from judges/audience carefully before coming up with an answer.

Guidelines and design to scientific poster presentation. The objective of scientific posters is to present laboratory work in scientific meetings. A poster is an excellent means of communicating scientific work, because it is a graphic representation of data. Posters should have focus points, and the intended message should be clearly conveyed through simple sections: Text, Tables, and Graphs. Posters should be clear, succinct, striking, and eye-catching. Colors should be used only where necessary. Use one font (Arial or Times New Roman) throughout. Fancy fonts should be avoided. All headings should have font size of 44, and be in bold capital letters. Size of Title may be a bit larger; subheading: Font size of 36, bold and caps. References and Acknowledgments, if any, should have font size of 24. Text should have font size between 24 and 30, in order to be legible from a distance of 3 to 6 feet. Do not use lengthy notes

PANEL DISCUSSION: FEEDBACK AND COMMENTS BY PARTICIPANTS

After all the presentations were made, Dr. Jagadeesh began a panel discussion that included all speakers. The discussion was aimed at what we do currently and could do in the future with respect to ‘developing a research question and then writing an effective thesis proposal/protocol followed by publication.’ Dr. Jagadeesh asked the following questions to the panelists, while receiving questions/suggestions from the participants and panelists.

• Does a Post-Graduate or Ph.D. student receive adequate training, either through an institutional course, a workshop of the present nature, or from the guide?
• Are these Post-Graduates self-taught (like most of us who learnt the hard way)?
• How are these guides trained? How do we train them to become more efficient mentors?
• Does a Post-Graduate or Ph.D. student struggle to find a method (s) to carry out studies? To what extent do seniors/guides help a post graduate overcome technical difficulties? How difficult is it for a student to find chemicals, reagents, instruments, and technical help in conducting studies?
• Analyses of data and interpretation: Most students struggle without adequate guidance.
• Thesis and publications frequently feature inadequate/incorrect statistical analyses and representation of data in tables/graphs. The student, their guide, and the reviewers all share equal responsibility.
• Who initiates and drafts the research paper? The Post-Graduate or their guide?
• What kind of assistance does a Post-Graduate get from the guide in finalizing a paper for publication?
• Does the guide insist that each Post-Graduate thesis yield at least one paper, and each Ph.D. thesis more than two papers, plus a review article?

The panelists and audience expressed a variety of views, but were unable to arrive at a decisive conclusion.

WHAT HAVE THE PARTICIPANTS LEARNED?

At the end of this fast-moving two-day workshop, the participants had opportunities in learning the following topics:

• Sequential steps in developing a study protocol, from choosing a research topic to developing research questions and a hypothesis.
• Study protocols on different topics in their subject of specialization
• Searching and reviewing the literature
• Appropriate statistical analyses in biomedical research
• Scientific ethics in publication
• Writing and understanding the components of a research paper (IMRaD)
• Recognizing the value of good title, running title, abstract, key words, etc
• Importance of Tables and Figures in the Results section, and their importance in describing findings
• Evidence-based Discussion in a research paper
• Language and style in writing a paper and expert tips on getting it published
• Presentation of research findings at a conference (oral and poster).

Overall, the workshop was deemed very helpful to participants. The participants rated the quality of workshop from “ satisfied ” to “ very satisfied .” A significant number of participants were of the opinion that the time allotted for each presentation was short and thus, be extended from the present two days to four days with adequate time to ask questions. In addition, a ‘hands-on’ session should be introduced for writing a proposal and manuscript. A large number of attendees expressed their desire to attend a similar workshop, if conducted, in the near future.

ACKNOWLEDGMENT

We gratefully express our gratitude to the Organizing Committee, especially Professors K. Chinnasamy, B. G. Shivananda, N. Udupa, Jerad Suresh, Padma Parekh, A. P. Basavarajappa, Mr. S. V. Veerramani, Mr. J. Jayaseelan, and all volunteers of the SRM University. We thank Dr. Thomas Papoian (US FDA) for helpful comments on the manuscript.

The opinions expressed herein are those of Gowraganahalli Jagadeesh and do not necessarily reflect those of the US Food and Drug Administration

Source of Support: Nil

Conflict of Interest: None declared.

Home » Blog » Comprehensive Guide to Research Methodology – Design | Methods | Best Practices

Comprehensive Guide to Research Methodology – Design | Methods | Best Practices

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• Last Updated on 16 September, 2024

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Table of Contents

• Introduction
• Steps in Research Process
• Classification of Research Design

1. Introduction

This article describes the research process and different research designs in detail. Management and social science research, like other forms of scientific inquiry, require a structured sequence of highly interrelated steps (Zigmund et al., 2010). The research process involves a series of steps or actions essential for the smooth conduct of any research. The figure below illustrates the sequence of the research process. It is to be noted that these steps are not a road map to all kinds of research. Basically, it is applicable for deductive or functionalist research, and it can or needs to be revised to suit the requirements of a specific project. The research process doesn’t need to be followed successively; rather, the steps overlap frequently and are interrelated. The research process offers a comprehensive guideline that can be referred to for any management and social science research. It may happen that later stages can be accomplished before the earlier stages.

The steps involved in the research process are neither mutually exclusive nor separate and distinct. The selection of a research topic at the outset, defining the research problem and objectives, influences the selection of a sample and data collection. The sample selection may affect the design of questionnaire items. For example, suppose an organization wants to know the cause of attrition among lower-category employees with low educational qualifications. In that case, the wording for the questionnaire will be easier than for people in top management positions with professional educational qualifications. The steps may differ based on the objectives of the research. However, research based on deductive logic should follow the steps outlined below:

2. Steps in Research Process

• Problem Identification
• Literature Review
• Formulating Research Questions
• Research Design
• Data Collection
• Data Analysis
• Conclusions and Report Writing.

The quest for research must always be triggered by the longing to explore and gain more knowledge and understanding. The management dilemma encourages the need for a decision. The need may arise owing to the cause that the researchers want to discover or reestablish certain relationships. The orientation might be to solve immediate management issues, discover something new, or have purely academic intentions. For instance, in an organization, the manager may want to know the reason for high attrition and lack of job satisfaction, or a retail store may survey the post-purchase satisfaction among the customers.

2.1 Research Problem Identification

Defining the research problem is the first step in the research process. The researchers get the proper direction to conduct their research by first understanding the research problems. Hence, a well-defined research problem is crucial. When the problem is discovered, researchers and management can take further steps to define the problem clearly and precisely. A problem defined with accuracy and conscience helps the researchers utilize the available resources effectively. It is imperative for researchers to explore what exactly is the problem and what are the objectives of the research. The rule generally followed to define the research problem is that the definition should permit the researchers to acquire all details required to address the managerial issues and show guidelines for finding a solution. The researcher should be careful not to define the problem too broadly or narrowly. Examples of broad managerial problems are defining a strategy for enhancing organizational performance and a strategy to elevate the organization’s brand equity. An example of a narrow definition of a problem is how to match competitors’ recruitment strategies. To overcome the possibility of both errors while defining the research problem, the researchers must define the problem with broad, popular terms and devise its components. The broad general statement helps the researchers get a sound perspective on the research problem and avoid the error of defining the problem narrowly. On the other side, the specific component helps to identify the key aspects of the research problem, extend a transparent guideline to proceed further and avoid the error of defining the problem too broadly. In management and social science research, broad management problems need to be converted to information-oriented research problems that focus more on the cause than the symptoms. Some examples of managerial problems converted to research problems are presented in Table below. The conversion of management dilemma to managerial questions and further to research questions can be carried out through exploratory research. Such research incorporates an examination of past research studies, a review of extant literature and organizational records and interviewing experts (Cooper et al., 2016).

2.2 Literature Review

Exploring the existing literature is critical in the research process. Researchers must explore and investigate extant literature to observe whether other researchers have already addressed the identified research problem. A literature review is a systematic search of published work, including periodicals, books, journal papers (conceptual and empirical), and reports, representing theory and empirical work about the research problem and topic at hand. A survey of existing literature is customary in applied research and is an elementary requirement of a basic research report. The internet, electronic databases, websites, and e-library help the researcher to carry out literature surveys systematically and easily.

The literature review aims to study the existing state of knowledge in the domain of interest, to picture key authors, theories, methods, topics, and findings in that domain, and to explore the gaps in knowledge in that domain. A literature review conducted systematically reveals whether initial research questions have already gained substantial attention in the extant literature, whether more interesting newer research questions are available, whether past studies have consistent findings or contradictions exist, flaws in the body of research that the researchers can address, and whether the initial research questions need to be revised as per the findings of the literature review. Furthermore, the review can answer the proposed research questions and help identify theories used in previous studies to address similar research questions. For example, for an organization interested in determining the true cause of turnover, the researcher will study extensively the existing literature on attrition and its causes. By studying relevant journal articles, books, and book chapters, the researcher will discover the causes of attrition in general, find out the existing gaps, and suggest the management carry forward the research to find causes specific to the organization.

As deductive research primarily involves theory testing, the researchers must identify one or more theories that can illuminate the proposed research questions. Through an extensive literature review, researchers may uncover various concepts and constructs related to the phenomenon of interest. A theory will extend support to constructs/variables that are logically relevant to the chosen phenomenon. In the deductive approach, researchers use theory/theories as the logical basis for hypothesis testing. However, researchers must carefully select the theories appropriate for the identified problem to be studied. The hypotheses need to be logically formulated and connected to the research objectives.

2.3 Formulating Research Questions

After problem identification and clarification, with or without an exploratory research approach, the researchers should derive the research objectives. Cautious attention to problem definition helps the researchers devise proper research objectives. Research objectives are the goal to be achieved through research. The research objective drives the research process further. A well-devised research objective enhances the possibility of gathering, relevant information and avoiding unwanted information. The research objectives can be properly developed with the consensus of the researchers and management on the actual managerial and business problems. The researcher should ensure that the research objectives are clearly stated, appropriate, and will yield germane information. The research objective may involve exploring the likelihood of venturing into a new market or may necessitate examining the effect of a new organizational policy on employee performance. The nature and types of objectives lead to choosing an appropriate research design.

Research Objectives:  Research objectives represent the goal of the research the researchers want to accomplish.

2.3.1 Suitable Research Questions

Research questions are important to conduct effective research. Without a clear research question, the researcher may face the risk of unfocused research and will not be sure of what the research is about. Research questions are refined descriptions of the components of the research problem. These are questions related to behavior, events or phenomena of interest that the researchers search for answers in their research. Examples include what factors motivate the employees in an organization to apply the gained knowledge back to their jobs or what needs to be done to enhance the creativity of school-going students. Research questions can best state the objectives of the research. Each component of the research problem needs to be broken down into sub-parts or research questions. Research questions inquire about the information essential concerning the problem components. Properly answered research questions will lead to effective decision-making. While formulating research questions, researchers should be guided by the problem statement, theoretical background, and analytical framework.

Sources of Research Questions

• Extant Literature
• Personal experience
• Societal issues
• Managerial problems
• New theories
• Technological advancement
• Empirical cases
• Contradictory finding

2.3.1.1 Significance of Research Questions

Research questions are critical because they guide scientific and systematic literature search, the decision about appropriate research design, the decision about data collection and target audience, data analysis, selection of right tools and techniques and overall to move in the right direction.

The researcher can utilize different sources for formulating research questions, such as extant literature, personal experience, societal issues, managerial problems, new theories, technological advancement, and contradictory findings. The research question must portray certain attributes. Research questions in quantitative research are more specific compared to qualitative research. Sometimes, some qualitative research follows an open approach without any research questions. The main steps involved in formulating research questions are illustrated in Figure below.

Criteria of Effective Research Questions

• Rateability
• Systematic and logical
• Significant
• Fascinating
• Logical association among variables

The sequence in selecting research questions suggests that the researchers are engrossed in a process of progressive focusing down when developing the research questions. It helps them to slide down from the general research area to research questions. While formulating the research questions, the researchers should understand that ending a research question with a question mark is essential. Without a question mark, a statement cannot be considered as a research question. It is quite possible that the researchers may not get answers to all research questions. The research questions need to be related to each other.

2.4 Planning the Research Design

After formulating research problems and literature surveys, the next stage in the research process is to develop the research design. Research design is the blueprint of research activities to answer research questions. It is a master plan that includes research methods and procedures for gathering and analyzing the relevant information with minimum cost, time, and effort. A research design extends a plan for carrying out the research. The researchers need to decide the source to collect information, the techniques of research design (survey or experiment), sampling techniques, and the cost and schedule of the research. The success of these objectives depends on the purpose of the research. Usually, research purposes are segregated into four types: exploration, description, diagnosis, and experimentation.

There are varied designs, such as experimental or non-experimental hypotheses testing (details of different research designs are outlined in section 2.3 in this chapter). There are four primary research methods for descriptive and causal research: survey, experiments, secondary data, and observations. The selection of an appropriate research method relies on the research objectives, available data sources, the cost and effort of collecting data, and the importance of managerial decisions. If the research objective is exploration, a flexible research design can extend better opportunities to investigate different aspects of the research problem. On the other hand, if the intention is simply to describe any situation or phenomena of interest to examine the relationship between two or more variables, the appropriate design should prioritize minimizing bias and maximizing reliability in data collection and analysis. For example, suppose a researcher wants to conduct exploratory research to know the different types of arthritis common in India. In that case, it may require a flexible design relying on secondary data from hospital records or discussions with doctors or other experts to reach conclusions. However, to invent COVID-vaccination and medicine for the COVID-19 virus, the researchers conducted varied experiments to reach a conclusion.

2.4.1 Hypotheses Development

Exploratory research helps the researchers define the research questions, key variables, and theoretical underpinnings and formulate hypotheses if required in the research. The hypotheses must be logically derived based on the research questions and linked to research objectives. A hypothesis is a tentative proposition regarding a research phenomenon. It may be a tentative statement that indicates an association between two or more variables, guided by any supportive theory, theoretical framework, or analytical model. It is a viable answer to the research questions framed by the researchers. Hypotheses are statements of relationships or propositions that are declarative and can be tested with empirical data. Some examples are:

H 1 : Training influences organizational performance.

H 2 : Training enhances employee performance.

For two more research questions i.e., “to what extent does brand love determine purchase intention?” and “does age and family background moderate the relationship?”, the hypotheses are:

H 1 : Brand love is related to purchase intention.

H 2 : Age and Family status moderate the association between brand love and purchase intention. Figure below provides a pictorial representation of the hypotheses drawn.

However, it is not always feasible for researchers to formulate hypotheses in all situations. Sometimes, researchers may lack all relevant information, and theoretical support may not be available to formulate the hypotheses.

2.5 Sampling Design

This stage of the research process involves an investigation of the population under study. A complete investigation of the population under study is known as a census inquiry. Usually, in census investigation, all units or items of the population are studied with high accuracy and reliability. However, it is usually not practicable and feasible for the researchers to study the entire population. Researchers usually prefer to investigate small, representative subgroups from the population known as sample. The procedure to select the sub-groups/samples is called sampling design. Sampling entails the process of drawing conclusions based on a subgroup of the population. Hence, the sample is a subset of the population. The first question that needs to be addressed in sampling is “who is to be included in the sample?” and this requires the identification of the target population under study. It is difficult for the researcher to define the population and sampling unit. For example, if a researcher wants to investigate the financial savings and vehicle loan association survey. In that case, individuals with existing accounts will be taken, and this sample unit represents the existing customers and not the potential customers. Hence, it is critical in sampling design to determine the specific target population.

Secondly, the issue that concerns the researchers in sampling design is selecting an appropriate sample size, and the third concern is selecting the sampling units. Researchers need to address these concerns to justify the research. Samples can be selected either using probability sampling techniques or non-probability sampling techniques. There are four types of probability sampling such as simple random, systematic, stratified, and cluster sampling. Non-probability sampling includes convenience, judgmental, quota, and snowball sampling. Depending on the objective, researchers should select the appropriate sampling techniques for their study.

2.6 Fieldwork and Gathering Data

After the formalization of the sampling plan, the fieldwork and data-gathering stage begins. The researcher gathers data after finalizing what to research, among whom, and which method to use. Data gathering involves the process of information collection. Different data collection instruments are available for researchers to collect information or data. Broadly, there are two ways to collect data, such as primary and secondary data collection methods. Primary data include data collected firsthand and are original. Varied methods are available for primary data collection, such as structured and unstructured interviews, focused group discussion, observation, and survey using a structured questionnaire. The data can be collected offline or online. Secondary data included information collected from published or unpublished sources that were already available. Some secondary data collection sources are articles, magazines, company records, expert opinion survey data, feedback of customers, government data, and past research on the subject. For example, to conduct a survey of job satisfaction in an organization, the researcher may circulate a printed questionnaire offline or mail the questionnaire to the selected respondents following an appropriate sampling technique.

Another example could be a study that investigates the purchase preference for luxury cars, and the base model demands primary and empirical information. However, another study that intended to describe the financial investment behavior of existing customers will use secondary data. At this stage, the researchers need to ensure the reliability and validity of the data obtained for the study.

2.7 Data Processing and Analysis

After data gathering, the data needs to be converted or properly coded to answer the research question under study. The information gathered in the data collection phase should be mined from the primary raw data. Data processing starts with data editing, coding, and tabulation. First, it is vital for the researchers to check the data collection forms for missing data, clarity, and consistency in categorization. The editing process involves problems associated with data, such as respondents’ response errors. Editing improves the quality of the data and makes the data usable for tabulation, analysis, and interpretation. Tabulation is a technical process in which classified data are presented in tables. Researchers use computers to feed data to a computer spreadsheet for data analysis. The preparation of a spreadsheet also requires lots of expertise and experience.

After coding the data, the next step is to analyze the data. Data analysis is the utilization of reasoning to make sense of data gathered. Ample statistical techniques are available for the researchers to analyze the data. Based on the research questions, objectives, study types, sampling framework used, data types, and degree of accuracy involved in the research, one can choose from parametric or non-parametric techniques for data analysis. Researchers may adopt univariate, bi-variate or multi-variate methods for data analysis. The analysis may include simple frequency analysis, multiple regression, or structural equation modeling. Different techniques are available for qualitative data, presented in Part 3 of this book.

2.8 Drawing Conclusion and Preparing a Report

After data analysis, the final stage in the research process is the interpretation of the results. The researcher requires analytical skills to interpret the statistical results, link the output with the research objectives, and state the implications of the result.

Research Design:  Research design is the blueprint/systematic steps to carry out research smoothly

Finally, researchers must communicate the result in the form of a report. The preparation of the final report needs to be done with the utmost care. The final report should include the identified research questions, research approach, data collection method, data analysis techniques, study findings, and implications for theory and practice. The structure of the report will be discussed in the last section of this book. The report should be prepared comprehensively to be usable by management or organizations for decision-making.

3. Classification of Research Design

This section highlights the classification of research design. As mentioned in the previous section, research design is the framework for carrying out management and other research. After the identification of a problem, the researchers formulate the research design. A good research design ensures the effectiveness of the research work. The choice of selecting an appropriate design relies on the research objectives. The broad categorization of research design with sub-categorization is detailed in various sub-sections.

3.1 Exploratory Research Design

Methods to Conduct Exploratory Research

• Literature survey
• Secondary sources of data
• Experience survey
• Focused group discussions
• Observations
• Structured and unstructured interviews
• Pilot surveys
• Case Studies

Exploratory research design is the simplest form of research design. The researchers explore the true nature of the problem. When researchers aim to study a new area or examine a new interest, exploratory design is a good option. This research design is flexible and versatile in approach. The information required by the researchers is defined loosely and unstructured. Researchers carrying out qualitative research usually adopt exploratory research design. Exploratory research design serves three purposes (a) it helps the researchers to address their inquisitiveness and quest for better understanding (b) to assess the practicality of carrying out border research (c) and devise methods for further studies.

Methods to Conduct Descriptive Research

• Self-administered survey
• Phone survey
• Mail survey/online survey
• Observation
• Personal interview
• Telephone interview

Exploratory research design has paramount significance in management and social science research. They are crucial for researchers who want to study something new. To cite an example, during the COVID-19 pandemic, physical health, mental health, and safety of school and college-going children were a concern for most people. The online education system was the new normal at that time. Research studying the impact of digitalization, long time spent in online studies on students’ health and mental well-being during the COVID-19 pandemic, is of an exploratory kind. One of the disadvantages of exploratory research design is that researchers rarely get specific answers to the research questions.

3.2 Descriptive Research Design

The prime objective of descriptive research design is to describe certain situations or events. This type of design provides an extensive explanation of the research phenomena under study. In descriptive research, the researchers possess prior knowledge about the problem situations. The information is defined with clarity. This kind of research is preplanned and more structured than exploratory research. Researchers must formulate research questions properly and have clarity regarding the types of data needed and the procedure to be followed to achieve the research objectives. Researchers have the luxury of covering a large representative sample. Researchers must answer five Ws and one H – what, who, when, where, why, and how of research issues. What kind of information is required for the research, who are the target respondents, when the information will be collected, where to interact with the respondents, why information is collected from the respondents and how to collect data from the respondents. Descriptive research studies can be cross-sectional or longitudinal. The major objectives for the following descriptive research are given below.

• To explain the characteristics of certain groups such as the Indian population, employees, students, marketing personnel, organizations, sales persons. For example, a university to design a customized online higher studies course for working professionals needs a holistic profile of the interested population.
• To evaluate the portion of individuals in a specific population portraying a typical behavior. For instance, when a researcher is inclined to know the percentage of employees not interested in an online platform introduced for them in their organization.
• To predict for future. For instance, to know the future of physical retail stores due to the widespread expansion of online stores.
• To examine the extent to which management research variables relate to each other. For example, to what extent does work-life balance, salary, and conducive work environment enhance employee job satisfaction?

3.3 Causal Research Design

Usually, causal research design is adopted by researchers to explain causal relationships among phenomena under study. Causal research examines cause-and-effect relationships among variables. Causal research has certain criteria, as already discussed in Chapter 1. Causal research follows a planned and structured design like descriptive research. Though the magnitude of the relationship among variables is examined in descriptive research, the causal association cannot be explained through such research. Experimentation is one of the methods for carrying out causal research.

In causal research, the researchers usually examine the impact of one variable on another. The researchers try to explore the cause-and-effect relationship (nomothetic explanation). How can the researcher know whether cause and effect are associated? There are three criteria for a nomothetic causal relationship when (1) two or more variables are correlated, (2) the cause precedes the effect and (3) the absence of a plausible alternative explanation for the effect other than the proposed cause (Babbie, 2020). First, without establishing a correlation among two or more variables, causation cannot exist. Second, the cause should happen before the effect in time. For instance, it is more sensible to say that children’s religious affiliation is caused by their parents than to reflect that parents’ religious affiliation is due to children; even in some cases, it is plausible that children may convert to other religions later with their parent’s permission. The third significant condition for a causal relationship is that the effect cannot be attributed to any external third variable for establishing causation.

To cite one classic example, there is a causal association between sales of ice cream and death owing to drowning. Intake of more ice creams in summer does lead to a higher death rate due to drowning. The third intervening variable that causes higher death is season or temperature. In summer, higher deaths occur due to swimming and not because of taking ice-creams. The intervening variable season or temperature causes a higher death rate.

To establish a reliable causal relationship among two or more variables, other influencing variables must be controlled to neutralize their impact on the studied variables. For example, to study the effect of factors influencing training transfer in soft skill training, the other intervening variables such as age, gender, and educational qualification need to be controlled. This kind of research sometimes demands experimentation to establish causality. In most cases, causal research is quantitative and needs statistical hypothesis testing.

3.4 Experimental Research Design

Experimental research aims to examine the cause-effect relationship in a controlled setting by isolating the cause from the effect in time. The three criteria suggested by John Stuart Mill mirror in experimental research. In experimental research, the cause is administered to one group of subjects, known as the treatment group and not to the control group, and the researchers observe the difference in mean effect among the subjects of both groups. Whether variation in the cause is connected to variation in effect is observed. To be more specific, the researcher manipulates the independent variable and examines the change in the dependent variable, keeping other variables constant. Researchers used varied methods during the experiments to reduce the plausible effect of other explanations for the effect, along with ancillary methods to investigate the plausibility of those that cannot be ruled out. It is vital in experimental studies to control the extraneous and confounding variables while carrying out the experiments. Ignorance of such variables may lead to spurious relationships among studied variables. However, bringing many of the variables under experimental control is impossible. For example, personal characteristics of the subject like age, sex, intelligence, beliefs and persona. In such cases, the researchers must observe natural variations in the variables of concern. Then, statistical procedures are used to rule out the plausible impact of uncontrolled factors.

Experimental Research Design:  An experiment is a method of collecting evidence to indicate the effect of one variable on another.

Experimental research design can be conducted in a laboratory setting (laboratory experiment) or in a field setting (field experiments) where the phenomena of research interest happen. As an example, one of the most talked about and controversial experiments conducted on understanding human behavior has been the Stanford Prison Experiments, which took place at Stanford University in 1971. The experiments were funded by the US Office of Naval Research, and the principal investigator for the same was Prof Phillip Zimbardo. The major purpose of these experiments was to understand how norms develop and social expectations about roles shape group behavior. Experimental studies are segregated into four categories such as pre-experimental, true-experimental, quasi-experimental and statistical design.

3.4.1 Correlation, Causation and Cofounds

Correlation cannot be treated as causation, and correlation does not always prove causation. In correlation, it is unclear which variable comes first or whether any alternative explanation exists for the assumed effect. Two variables may be correlated due to chance. Correlation is symmetric, while causation is asymmetric. Two variables may be co-related, but their relationship may be affected by a third variable called cofounds. For example, let’s say that high salary and high educational qualifications are correlated. It is difficult to say with confirmation which comes first. Whether a high educational qualification leads to a high salary, or a high salary leads to a high educational qualification. Both possibilities can hold true and necessitate further investigation. Until researchers conclude through their investigation, a mere correlation among these two variables will not give a clear picture of their causal relationship. There is also the possibility of an alternative explanation for the relationship between high salary and high educational qualifications. The link may be due to a third variable called intellect, which results in high salary and high educational qualifications.

In management research, social science, and natural science, three significant pairs of components are required for experimentation: Experimental and control group, independent and dependent variable, and pre-test and post-test.

3.4.1.1 Experimental and Control Group

The group in which an experimental treatment is administered is known as the experimental or treatment group. In contrast, the group in which no experiment is administered is known as the control group. Using control groups enables the researchers to assess the experiment’s effects. For example, suppose a researcher wants to study the impact of rewards on employee productivity in an organization. In that case, the researcher can experiment with two groups of employees. One group will be given external rewards, known as the experimental group, and the other group (control group) will provide no external rewards. Then, the researcher can investigate the causal association between rewards on employees’ productivity through this experiment. The use of a control group is quite common in medical science research. In social science and management research, the use of control groups and experimental studies became popular with several experiments conducted in the late 1920s and early 1930s by F. J. Roethlisberger and W. J. Dickson (1939) to discover the changes required in working conditions to enhance employee satisfaction and productivity. Their series of experiments resulted in the Hawthorne effect.

3.4.1.2 Independent and Dependent Variables

In experimental research, the researchers study the impact of an independent variable on the dependent variable. Usually, experimental stimuli, whether present or absent, are considered independent variables. Independent variables are manipulated in the study, and their effects are assessed and compared. The researchers compare outcomes when the stimulus is present and not present. Hence, the independent variable is the cause, and the dependent variable is the presumed effect. It is to be noted that the independent variable in one study may serve as a dependent variable in another study. For example, an experiment intends to explore the causality between high salary and job satisfaction, job satisfaction is the dependent variable. However, in another experiment designed to explore the causality between job satisfaction and employee productivity, job satisfaction is the independent variable.

3.4.1.3 Pre- and Post-test

In an experiment, the experimenters measure the variable before conducting the experiment on the group known as the pre-test and measure the variable after conducting the experiments is called as post-test. Hence, subjects are exposed to a stimulus called a dependent variable (pre-testing), then exposed to a stimulus, i.e., independent variable, and again assessed with a dependent variable (post-testing). Any discrepancies between the two measurements of dependent variables are ascribed to the independent variable.

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