Example: Factorial design applied in optimisation technique.
To meet the ethical considerations, you need to ensure that.
Collect the data by using suitable data collection according to your experiment’s requirement, such as observations, case studies , surveys , interviews , questionnaires, etc. Analyse the obtained information.
Write the report of your research. Present, conclude, and explain the outcomes of your study .
What is the first step in conducting an experimental research.
The first step in conducting experimental research is to define your research question or hypothesis. Clearly outline the purpose and expectations of your experiment to guide the entire research process.
Analysis of Variance or ANOVA is a statistical test that uses means of two or more groups to analyse the difference. Here is all you need to know about it.
Descriptive research is carried out to describe current issues, programs, and provides information about the issue through surveys and various fact-finding methods.
Statistical power is a decision by a researcher/statistician that results of a study/experiment can be explained by factors other than chance alone. The statistical power of a study is also referred to as its sensitivity in some cases.
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Experiments are part of the scientific method that helps to decide the fate of two or more competing hypotheses or explanations on a phenomenon. The term ‘experiment’ arises from Latin, Experiri, which means, ‘to try’. The knowledge accrues from experiments differs from other types of knowledge in that it is always shaped upon observation or experience. In other words, experiments generate empirical knowledge. In fact, the emphasis on experimentation in the sixteenth and seventeenth centuries for establishing causal relationships for various phenomena happening in nature heralded the resurgence of modern science from its roots in ancient philosophy spearheaded by great Greek philosophers such as Aristotle.
The strongest arguments prove nothing so long as the conclusions are not verified by experience. Experimental science is the queen of sciences and the goal of all speculation . Roger Bacon (1214–1294)
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Best, J.W. and Kahn, J.V. 1993. Research in Education (7th Ed., Indian Reprint, 2004). Prentice–Hall of India, New Delhi, 435p.
Google Scholar
Campbell, D. and Stanley, J. 1963. Experimental and quasi-experimental designs for research. In: Gage, N.L., Handbook of Research on Teaching. Rand McNally, Chicago, pp. 171–247.
Chandel, S.R.S. 1991. A Handbook of Agricultural Statistics. Achal Prakashan Mandir, Kanpur, 560p.
Cox, D.R. 1958. Planning of Experiments. John Wiley & Sons, New York, 308p.
Fathalla, M.F. and Fathalla, M.M.F. 2004. A Practical Guide for Health Researchers. WHO Regional Publications Eastern Mediterranean Series 30. World Health Organization Regional Office for the Eastern Mediterranean, Cairo, 232p.
Fowkes, F.G.R., and Fulton, P.M. 1991. Critical appraisal of published research: Introductory guidelines. Br. Med. J. 302: 1136–1140.
Gall, M.D., Borg, W.R., and Gall, J.P. 1996. Education Research: An Introduction (6th Ed.). Longman, New York, 788p.
Gomez, K.A. 1972. Techniques for Field Experiments with Rice. International Rice Research Institute, Manila, Philippines, 46p.
Gomez, K.A. and Gomez, A.A. 1984. Statistical Procedures for Agricultural Research (2nd Ed.). John Wiley & Sons, New York, 680p.
Hill, A.B. 1971. Principles of Medical Statistics (9th Ed.). Oxford University Press, New York, 390p.
Holmes, D., Moody, P., and Dine, D. 2010. Research Methods for the Bioscience (2nd Ed.). Oxford University Press, Oxford, 457p.
Kerlinger, F.N. 1986. Foundations of Behavioural Research (3rd Ed.). Holt, Rinehart and Winston, USA. 667p.
Kirk, R.E. 2012. Experimental Design: Procedures for the Behavioural Sciences (4th Ed.). Sage Publications, 1072p.
Kothari, C.R. 2004. Research Methodology: Methods and Techniques (2nd Ed.). New Age International, New Delhi, 401p.
Kumar, R. 2011. Research Methodology: A Step-by step Guide for Beginners (3rd Ed.). Sage Publications India, New Delhi, 415p.
Leedy, P.D. and Ormrod, J.L. 2010. Practical Research: Planning and Design (9th Ed.), Pearson Education, New Jersey, 360p.
Marder, M.P. 2011. Research Methods for Science. Cambridge University Press, 227p.
Panse, V.G. and Sukhatme, P.V. 1985. Statistical Methods for Agricultural Workers (4th Ed., revised: Sukhatme, P.V. and Amble, V. N.). ICAR, New Delhi, 359p.
Ross, S.M. and Morrison, G.R. 2004. Experimental research methods. In: Jonassen, D.H. (ed.), Handbook of Research for Educational Communications and Technology (2nd Ed.). Lawrence Erlbaum Associates, New Jersey, pp. 10211043.
Snedecor, G.W. and Cochran, W.G. 1980. Statistical Methods (7th Ed.). Iowa State University Press, Ames, Iowa, 507p.
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Thomas, C.G. (2021). Experimental Research. In: Research Methodology and Scientific Writing . Springer, Cham. https://doi.org/10.1007/978-3-030-64865-7_5
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Since school days’ students perform scientific experiments that provide results that define and prove the laws and theorems in science. These experiments are laid on a strong foundation of experimental research designs.
An experimental research design helps researchers execute their research objectives with more clarity and transparency.
In this article, we will not only discuss the key aspects of experimental research designs but also the issues to avoid and problems to resolve while designing your research study.
Table of Contents
Experimental research design is a framework of protocols and procedures created to conduct experimental research with a scientific approach using two sets of variables. Herein, the first set of variables acts as a constant, used to measure the differences of the second set. The best example of experimental research methods is quantitative research .
Experimental research helps a researcher gather the necessary data for making better research decisions and determining the facts of a research study.
A researcher can conduct experimental research in the following situations —
To publish significant results, choosing a quality research design forms the foundation to build the research study. Moreover, effective research design helps establish quality decision-making procedures, structures the research to lead to easier data analysis, and addresses the main research question. Therefore, it is essential to cater undivided attention and time to create an experimental research design before beginning the practical experiment.
By creating a research design, a researcher is also giving oneself time to organize the research, set up relevant boundaries for the study, and increase the reliability of the results. Through all these efforts, one could also avoid inconclusive results. If any part of the research design is flawed, it will reflect on the quality of the results derived.
Based on the methods used to collect data in experimental studies, the experimental research designs are of three primary types:
A research study could conduct pre-experimental research design when a group or many groups are under observation after implementing factors of cause and effect of the research. The pre-experimental design will help researchers understand whether further investigation is necessary for the groups under observation.
Pre-experimental research is of three types —
A true experimental research design relies on statistical analysis to prove or disprove a researcher’s hypothesis. It is one of the most accurate forms of research because it provides specific scientific evidence. Furthermore, out of all the types of experimental designs, only a true experimental design can establish a cause-effect relationship within a group. However, in a true experiment, a researcher must satisfy these three factors —
This type of experimental research is commonly observed in the physical sciences.
The word “Quasi” means similarity. A quasi-experimental design is similar to a true experimental design. However, the difference between the two is the assignment of the control group. In this research design, an independent variable is manipulated, but the participants of a group are not randomly assigned. This type of research design is used in field settings where random assignment is either irrelevant or not required.
The classification of the research subjects, conditions, or groups determines the type of research design to be used.
Experimental research allows you to test your idea in a controlled environment before taking the research to clinical trials. Moreover, it provides the best method to test your theory because of the following advantages:
There is no order to this list, and any one of these issues can seriously compromise the quality of your research. You could refer to the list as a checklist of what to avoid while designing your research.
Usually, researchers miss out on checking if their hypothesis is logical to be tested. If your research design does not have basic assumptions or postulates, then it is fundamentally flawed and you need to rework on your research framework.
Without a comprehensive research literature review , it is difficult to identify and fill the knowledge and information gaps. Furthermore, you need to clearly state how your research will contribute to the research field, either by adding value to the pertinent literature or challenging previous findings and assumptions.
Statistical results are one of the most trusted scientific evidence. The ultimate goal of a research experiment is to gain valid and sustainable evidence. Therefore, incorrect statistical analysis could affect the quality of any quantitative research.
This is one of the most basic aspects of research design. The research problem statement must be clear and to do that, you must set the framework for the development of research questions that address the core problems.
Every study has some type of limitations . You should anticipate and incorporate those limitations into your conclusion, as well as the basic research design. Include a statement in your manuscript about any perceived limitations, and how you considered them while designing your experiment and drawing the conclusion.
The most important yet less talked about topic is the ethical issue. Your research design must include ways to minimize any risk for your participants and also address the research problem or question at hand. If you cannot manage the ethical norms along with your research study, your research objectives and validity could be questioned.
In an experimental design, a researcher gathers plant samples and then randomly assigns half the samples to photosynthesize in sunlight and the other half to be kept in a dark box without sunlight, while controlling all the other variables (nutrients, water, soil, etc.)
By comparing their outcomes in biochemical tests, the researcher can confirm that the changes in the plants were due to the sunlight and not the other variables.
Experimental research is often the final form of a study conducted in the research process which is considered to provide conclusive and specific results. But it is not meant for every research. It involves a lot of resources, time, and money and is not easy to conduct, unless a foundation of research is built. Yet it is widely used in research institutes and commercial industries, for its most conclusive results in the scientific approach.
Have you worked on research designs? How was your experience creating an experimental design? What difficulties did you face? Do write to us or comment below and share your insights on experimental research designs!
Randomization is important in an experimental research because it ensures unbiased results of the experiment. It also measures the cause-effect relationship on a particular group of interest.
Experimental research design lay the foundation of a research and structures the research to establish quality decision making process.
There are 3 types of experimental research designs. These are pre-experimental research design, true experimental research design, and quasi experimental research design.
The difference between an experimental and a quasi-experimental design are: 1. The assignment of the control group in quasi experimental research is non-random, unlike true experimental design, which is randomly assigned. 2. Experimental research group always has a control group; on the other hand, it may not be always present in quasi experimental research.
Experimental research establishes a cause-effect relationship by testing a theory or hypothesis using experimental groups or control variables. In contrast, descriptive research describes a study or a topic by defining the variables under it and answering the questions related to the same.
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Experimental design refers to how participants are allocated to different groups in an experiment. Types of design include repeated measures, independent groups, and matched pairs designs.
Probably the most common way to design an experiment in psychology is to divide the participants into two groups, the experimental group and the control group, and then introduce a change to the experimental group, not the control group.
The researcher must decide how he/she will allocate their sample to the different experimental groups. For example, if there are 10 participants, will all 10 participants participate in both groups (e.g., repeated measures), or will the participants be split in half and take part in only one group each?
Three types of experimental designs are commonly used:
Independent measures design, also known as between-groups , is an experimental design where different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants.
This should be done by random allocation, ensuring that each participant has an equal chance of being assigned to one group.
Independent measures involve using two separate groups of participants, one in each condition. For example:
Repeated Measures design is an experimental design where the same participants participate in each independent variable condition. This means that each experiment condition includes the same group of participants.
Repeated Measures design is also known as within-groups or within-subjects design .
Suppose we used a repeated measures design in which all of the participants first learned words in “loud noise” and then learned them in “no noise.”
We expect the participants to learn better in “no noise” because of order effects, such as practice. However, a researcher can control for order effects using counterbalancing.
The sample would be split into two groups: experimental (A) and control (B). For example, group 1 does ‘A’ then ‘B,’ and group 2 does ‘B’ then ‘A.’ This is to eliminate order effects.
Although order effects occur for each participant, they balance each other out in the results because they occur equally in both groups.
A matched pairs design is an experimental design where pairs of participants are matched in terms of key variables, such as age or socioeconomic status. One member of each pair is then placed into the experimental group and the other member into the control group .
One member of each matched pair must be randomly assigned to the experimental group and the other to the control group.
Experimental design refers to how participants are allocated to an experiment’s different conditions (or IV levels). There are three types:
1. Independent measures / between-groups : Different participants are used in each condition of the independent variable.
2. Repeated measures /within groups : The same participants take part in each condition of the independent variable.
3. Matched pairs : Each condition uses different participants, but they are matched in terms of important characteristics, e.g., gender, age, intelligence, etc.
Read about each of the experiments below. For each experiment, identify (1) which experimental design was used; and (2) why the researcher might have used that design.
1 . To compare the effectiveness of two different types of therapy for depression, depressed patients were assigned to receive either cognitive therapy or behavior therapy for a 12-week period.
The researchers attempted to ensure that the patients in the two groups had similar severity of depressed symptoms by administering a standardized test of depression to each participant, then pairing them according to the severity of their symptoms.
2 . To assess the difference in reading comprehension between 7 and 9-year-olds, a researcher recruited each group from a local primary school. They were given the same passage of text to read and then asked a series of questions to assess their understanding.
3 . To assess the effectiveness of two different ways of teaching reading, a group of 5-year-olds was recruited from a primary school. Their level of reading ability was assessed, and then they were taught using scheme one for 20 weeks.
At the end of this period, their reading was reassessed, and a reading improvement score was calculated. They were then taught using scheme two for a further 20 weeks, and another reading improvement score for this period was calculated. The reading improvement scores for each child were then compared.
4 . To assess the effect of the organization on recall, a researcher randomly assigned student volunteers to two conditions.
Condition one attempted to recall a list of words that were organized into meaningful categories; condition two attempted to recall the same words, randomly grouped on the page.
Ecological validity.
The degree to which an investigation represents real-life experiences.
These are the ways that the experimenter can accidentally influence the participant through their appearance or behavior.
The clues in an experiment lead the participants to think they know what the researcher is looking for (e.g., the experimenter’s body language).
The variable the experimenter manipulates (i.e., changes) is assumed to have a direct effect on the dependent variable.
Variable the experimenter measures. This is the outcome (i.e., the result) of a study.
All variables which are not independent variables but could affect the results (DV) of the experiment. Extraneous variables should be controlled where possible.
Variable(s) that have affected the results (DV), apart from the IV. A confounding variable could be an extraneous variable that has not been controlled.
Randomly allocating participants to independent variable conditions means that all participants should have an equal chance of taking part in each condition.
The principle of random allocation is to avoid bias in how the experiment is carried out and limit the effects of participant variables.
Changes in participants’ performance due to their repeating the same or similar test more than once. Examples of order effects include:
(i) practice effect: an improvement in performance on a task due to repetition, for example, because of familiarity with the task;
(ii) fatigue effect: a decrease in performance of a task due to repetition, for example, because of boredom or tiredness.
Experimental research is the most familiar type of research design for individuals in the physical sciences and a host of other fields. This is mainly because experimental research is a classical scientific experiment, similar to those performed in high school science classes.
Imagine taking 2 samples of the same plant and exposing one of them to sunlight, while the other is kept away from sunlight. Let the plant exposed to sunlight be called sample A, while the latter is called sample B.
If after the duration of the research, we find out that sample A grows and sample B dies, even though they are both regularly wetted and given the same treatment. Therefore, we can conclude that sunlight will aid growth in all similar plants.
Experimental research is a scientific approach to research, where one or more independent variables are manipulated and applied to one or more dependent variables to measure their effect on the latter. The effect of the independent variables on the dependent variables is usually observed and recorded over some time, to aid researchers in drawing a reasonable conclusion regarding the relationship between these 2 variable types.
The experimental research method is widely used in physical and social sciences, psychology, and education. It is based on the comparison between two or more groups with a straightforward logic, which may, however, be difficult to execute.
Mostly related to a laboratory test procedure, experimental research designs involve collecting quantitative data and performing statistical analysis on them during research. Therefore, making it an example of quantitative research method .
The types of experimental research design are determined by the way the researcher assigns subjects to different conditions and groups. They are of 3 types, namely; pre-experimental, quasi-experimental, and true experimental research.
In pre-experimental research design, either a group or various dependent groups are observed for the effect of the application of an independent variable which is presumed to cause change. It is the simplest form of experimental research design and is treated with no control group.
Although very practical, experimental research is lacking in several areas of the true-experimental criteria. The pre-experimental research design is further divided into three types
In this type of experimental study, only one dependent group or variable is considered. The study is carried out after some treatment which was presumed to cause change, making it a posttest study.
This research design combines both posttest and pretest study by carrying out a test on a single group before the treatment is administered and after the treatment is administered. With the former being administered at the beginning of treatment and later at the end.
In a static-group comparison study, 2 or more groups are placed under observation, where only one of the groups is subjected to some treatment while the other groups are held static. All the groups are post-tested, and the observed differences between the groups are assumed to be a result of the treatment.
The word “quasi” means partial, half, or pseudo. Therefore, the quasi-experimental research bearing a resemblance to the true experimental research, but not the same. In quasi-experiments, the participants are not randomly assigned, and as such, they are used in settings where randomization is difficult or impossible.
This is very common in educational research, where administrators are unwilling to allow the random selection of students for experimental samples.
Some examples of quasi-experimental research design include; the time series, no equivalent control group design, and the counterbalanced design.
The true experimental research design relies on statistical analysis to approve or disprove a hypothesis. It is the most accurate type of experimental design and may be carried out with or without a pretest on at least 2 randomly assigned dependent subjects.
The true experimental research design must contain a control group, a variable that can be manipulated by the researcher, and the distribution must be random. The classification of true experimental design include:
The first two of these groups are tested using the posttest-only method, while the other two are tested using the pretest-posttest method.
Experimental research examples are different, depending on the type of experimental research design that is being considered. The most basic example of experimental research is laboratory experiments, which may differ in nature depending on the subject of research.
During the semester, students in a class are lectured on particular courses and an exam is administered at the end of the semester. In this case, the students are the subjects or dependent variables while the lectures are the independent variables treated on the subjects.
Only one group of carefully selected subjects are considered in this research, making it a pre-experimental research design example. We will also notice that tests are only carried out at the end of the semester, and not at the beginning.
Further making it easy for us to conclude that it is a one-shot case study research.
Before employing a job seeker, organizations conduct tests that are used to screen out less qualified candidates from the pool of qualified applicants. This way, organizations can determine an employee’s skill set at the point of employment.
In the course of employment, organizations also carry out employee training to improve employee productivity and generally grow the organization. Further evaluation is carried out at the end of each training to test the impact of the training on employee skills, and test for improvement.
Here, the subject is the employee, while the treatment is the training conducted. This is a pretest-posttest control group experimental research example.
Let us consider an academic institution that wants to evaluate the teaching method of 2 teachers to determine which is best. Imagine a case whereby the students assigned to each teacher is carefully selected probably due to personal request by parents or due to stubbornness and smartness.
This is a no equivalent group design example because the samples are not equal. By evaluating the effectiveness of each teacher’s teaching method this way, we may conclude after a post-test has been carried out.
However, this may be influenced by factors like the natural sweetness of a student. For example, a very smart student will grab more easily than his or her peers irrespective of the method of teaching.
Experimental research contains dependent, independent and extraneous variables. The dependent variables are the variables being treated or manipulated and are sometimes called the subject of the research.
The independent variables are the experimental treatment being exerted on the dependent variables. Extraneous variables, on the other hand, are other factors affecting the experiment that may also contribute to the change.
The setting is where the experiment is carried out. Many experiments are carried out in the laboratory, where control can be exerted on the extraneous variables, thereby eliminating them.
Other experiments are carried out in a less controllable setting. The choice of setting used in research depends on the nature of the experiment being carried out.
Experimental research may include multiple independent variables, e.g. time, skills, test scores, etc.
Experimental research design can be majorly used in physical sciences, social sciences, education, and psychology. It is used to make predictions and draw conclusions on a subject matter.
Some uses of experimental research design are highlighted below.
The changes observed during this period are recorded and evaluated to determine its effectiveness. This process can be carried out using different experimental research methods.
The other person is placed in a room with a few other people, enjoying human interaction. There will be a difference in their behaviour at the end of the experiment.
For example, when finding it difficult to choose how to position a button or feature on the app interface, a random sample of product testers are allowed to test the 2 samples and how the button positioning influences the user interaction is recorded.
Data collection methods in experimental research are the different ways in which data can be collected for experimental research. They are used in different cases, depending on the type of research being carried out.
This type of study is carried out over a long period. It measures and observes the variables of interest without changing existing conditions.
When researching the effect of social interaction on human behavior, the subjects who are placed in 2 different environments are observed throughout the research. No matter the kind of absurd behavior that is exhibited by the subject during this period, its condition will not be changed.
This may be a very risky thing to do in medical cases because it may lead to death or worse medical conditions.
This procedure uses mathematical, physical, or computer models to replicate a real-life process or situation. It is frequently used when the actual situation is too expensive, dangerous, or impractical to replicate in real life.
This method is commonly used in engineering and operational research for learning purposes and sometimes as a tool to estimate possible outcomes of real research. Some common situation software are Simulink, MATLAB, and Simul8.
Not all kinds of experimental research can be carried out using simulation as a data collection tool . It is very impractical for a lot of laboratory-based research that involves chemical processes.
A survey is a tool used to gather relevant data about the characteristics of a population and is one of the most common data collection tools. A survey consists of a group of questions prepared by the researcher, to be answered by the research subject.
Surveys can be shared with the respondents both physically and electronically. When collecting data through surveys, the kind of data collected depends on the respondent, and researchers have limited control over it.
Formplus is the best tool for collecting experimental data using survey s. It has relevant features that will aid the data collection process and can also be used in other aspects of experimental research.
1. In experimental research, the researcher can control and manipulate the environment of the research, including the predictor variable which can be changed. On the other hand, non-experimental research cannot be controlled or manipulated by the researcher at will.
This is because it takes place in a real-life setting, where extraneous variables cannot be eliminated. Therefore, it is more difficult to conclude non-experimental studies, even though they are much more flexible and allow for a greater range of study fields.
2. The relationship between cause and effect cannot be established in non-experimental research, while it can be established in experimental research. This may be because many extraneous variables also influence the changes in the research subject, making it difficult to point at a particular variable as the cause of a particular change
3. Independent variables are not introduced, withdrawn, or manipulated in non-experimental designs, but the same may not be said about experimental research.
1. experimental research vs causal comparative.
Experimental research enables you to control variables and identify how the independent variable affects the dependent variable. Causal-comparative find out the cause-and-effect relationship between the variables by comparing already existing groups that are affected differently by the independent variable.
For example, in an experiment to see how K-12 education affects children and teenager development. An experimental research would split the children into groups, some would get formal K-12 education, while others won’t. This is not ethically right because every child has the right to education. So, what we do instead would be to compare already existing groups of children who are getting formal education with those who due to some circumstances can not.
When experimenting, you are trying to establish a cause-and-effect relationship between different variables. For example, you are trying to establish the effect of heat on water, the temperature keeps changing (independent variable) and you see how it affects the water (dependent variable).
For correlational research, you are not necessarily interested in the why or the cause-and-effect relationship between the variables, you are focusing on the relationship. Using the same water and temperature example, you are only interested in the fact that they change, you are not investigating which of the variables or other variables causes them to change.
3. experimental research vs descriptive research.
With experimental research, you alter the independent variable to see how it affects the dependent variable, but with descriptive research you are simply studying the characteristics of the variable you are studying.
So, in an experiment to see how blown glass reacts to temperature, experimental research would keep altering the temperature to varying levels of high and low to see how it affects the dependent variable (glass). But descriptive research would investigate the glass properties.
4. experimental research vs action research.
Experimental research tests for causal relationships by focusing on one independent variable vs the dependent variable and keeps other variables constant. So, you are testing hypotheses and using the information from the research to contribute to knowledge.
However, with action research, you are using a real-world setting which means you are not controlling variables. You are also performing the research to solve actual problems and improve already established practices.
For example, if you are testing for how long commutes affect workers’ productivity. With experimental research, you would vary the length of commute to see how the time affects work. But with action research, you would account for other factors such as weather, commute route, nutrition, etc. Also, experimental research helps know the relationship between commute time and productivity, while action research helps you look for ways to improve productivity
Conclusion .
Experimental research designs are often considered to be the standard in research designs. This is partly due to the common misconception that research is equivalent to scientific experiments—a component of experimental research design.
In this research design, one or more subjects or dependent variables are randomly assigned to different treatments (i.e. independent variables manipulated by the researcher) and the results are observed to conclude. One of the uniqueness of experimental research is in its ability to control the effect of extraneous variables.
Experimental research is suitable for research whose goal is to examine cause-effect relationships, e.g. explanatory research. It can be conducted in the laboratory or field settings, depending on the aim of the research that is being carried out.
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Published on May 20, 2021 by Pritha Bhandari . Revised on July 23, 2023.
A lab report conveys the aim, methods, results, and conclusions of a scientific experiment. The main purpose of a lab report is to demonstrate your understanding of the scientific method by performing and evaluating a hands-on lab experiment. This type of assignment is usually shorter than a research paper .
Lab reports are commonly used in science, technology, engineering, and mathematics (STEM) fields. This article focuses on how to structure and write a lab report.
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Structuring a lab report, introduction, other interesting articles, frequently asked questions about lab reports.
The sections of a lab report can vary between scientific fields and course requirements, but they usually contain the purpose, methods, and findings of a lab experiment .
Each section of a lab report has its own purpose.
Although most lab reports contain these sections, some sections can be omitted or combined with others. For example, some lab reports contain a brief section on research aims instead of an introduction, and a separate conclusion is not always required.
If you’re not sure, it’s best to check your lab report requirements with your instructor.
Professional editors proofread and edit your paper by focusing on:
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Your title provides the first impression of your lab report – effective titles communicate the topic and/or the findings of your study in specific terms.
Create a title that directly conveys the main focus or purpose of your study. It doesn’t need to be creative or thought-provoking, but it should be informative.
An abstract condenses a lab report into a brief overview of about 150–300 words. It should provide readers with a compact version of the research aims, the methods and materials used, the main results, and the final conclusion.
Think of it as a way of giving readers a preview of your full lab report. Write the abstract last, in the past tense, after you’ve drafted all the other sections of your report, so you’ll be able to succinctly summarize each section.
To write a lab report abstract, use these guiding questions:
Nitrogen is a necessary nutrient for high quality plants. Tomatoes, one of the most consumed fruits worldwide, rely on nitrogen for healthy leaves and stems to grow fruit. This experiment tested whether nitrogen levels affected tomato plant height in a controlled setting. It was expected that higher levels of nitrogen fertilizer would yield taller tomato plants.
Levels of nitrogen fertilizer were varied between three groups of tomato plants. The control group did not receive any nitrogen fertilizer, while one experimental group received low levels of nitrogen fertilizer, and a second experimental group received high levels of nitrogen fertilizer. All plants were grown from seeds, and heights were measured 50 days into the experiment.
The effects of nitrogen levels on plant height were tested between groups using an ANOVA. The plants with the highest level of nitrogen fertilizer were the tallest, while the plants with low levels of nitrogen exceeded the control group plants in height. In line with expectations and previous findings, the effects of nitrogen levels on plant height were statistically significant. This study strengthens the importance of nitrogen for tomato plants.
Your lab report introduction should set the scene for your experiment. One way to write your introduction is with a funnel (an inverted triangle) structure:
Begin by providing background information on your research topic and explaining why it’s important in a broad real-world or theoretical context. Describe relevant previous research on your topic and note how your study may confirm it or expand it, or fill a gap in the research field.
This lab experiment builds on previous research from Haque, Paul, and Sarker (2011), who demonstrated that tomato plant yield increased at higher levels of nitrogen. However, the present research focuses on plant height as a growth indicator and uses a lab-controlled setting instead.
Next, go into detail on the theoretical basis for your study and describe any directly relevant laws or equations that you’ll be using. State your main research aims and expectations by outlining your hypotheses .
Based on the importance of nitrogen for tomato plants, the primary hypothesis was that the plants with the high levels of nitrogen would grow the tallest. The secondary hypothesis was that plants with low levels of nitrogen would grow taller than plants with no nitrogen.
Your introduction doesn’t need to be long, but you may need to organize it into a few paragraphs or with subheadings such as “Research Context” or “Research Aims.”
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A lab report Method section details the steps you took to gather and analyze data. Give enough detail so that others can follow or evaluate your procedures. Write this section in the past tense. If you need to include any long lists of procedural steps or materials, place them in the Appendices section but refer to them in the text here.
You should describe your experimental design, your subjects, materials, and specific procedures used for data collection and analysis.
Briefly note whether your experiment is a within-subjects or between-subjects design, and describe how your sample units were assigned to conditions if relevant.
A between-subjects design with three groups of tomato plants was used. The control group did not receive any nitrogen fertilizer. The first experimental group received a low level of nitrogen fertilizer, while the second experimental group received a high level of nitrogen fertilizer.
Describe human subjects in terms of demographic characteristics, and animal or plant subjects in terms of genetic background. Note the total number of subjects as well as the number of subjects per condition or per group. You should also state how you recruited subjects for your study.
List the equipment or materials you used to gather data and state the model names for any specialized equipment.
List of materials
35 Tomato seeds
15 plant pots (15 cm tall)
Light lamps (50,000 lux)
Nitrogen fertilizer
Measuring tape
Describe your experimental settings and conditions in detail. You can provide labelled diagrams or images of the exact set-up necessary for experimental equipment. State how extraneous variables were controlled through restriction or by fixing them at a certain level (e.g., keeping the lab at room temperature).
Light levels were fixed throughout the experiment, and the plants were exposed to 12 hours of light a day. Temperature was restricted to between 23 and 25℃. The pH and carbon levels of the soil were also held constant throughout the experiment as these variables could influence plant height. The plants were grown in rooms free of insects or other pests, and they were spaced out adequately.
Your experimental procedure should describe the exact steps you took to gather data in chronological order. You’ll need to provide enough information so that someone else can replicate your procedure, but you should also be concise. Place detailed information in the appendices where appropriate.
In a lab experiment, you’ll often closely follow a lab manual to gather data. Some instructors will allow you to simply reference the manual and state whether you changed any steps based on practical considerations. Other instructors may want you to rewrite the lab manual procedures as complete sentences in coherent paragraphs, while noting any changes to the steps that you applied in practice.
If you’re performing extensive data analysis, be sure to state your planned analysis methods as well. This includes the types of tests you’ll perform and any programs or software you’ll use for calculations (if relevant).
First, tomato seeds were sown in wooden flats containing soil about 2 cm below the surface. Each seed was kept 3-5 cm apart. The flats were covered to keep the soil moist until germination. The seedlings were removed and transplanted to pots 8 days later, with a maximum of 2 plants to a pot. Each pot was watered once a day to keep the soil moist.
The nitrogen fertilizer treatment was applied to the plant pots 12 days after transplantation. The control group received no treatment, while the first experimental group received a low concentration, and the second experimental group received a high concentration. There were 5 pots in each group, and each plant pot was labelled to indicate the group the plants belonged to.
50 days after the start of the experiment, plant height was measured for all plants. A measuring tape was used to record the length of the plant from ground level to the top of the tallest leaf.
In your results section, you should report the results of any statistical analysis procedures that you undertook. You should clearly state how the results of statistical tests support or refute your initial hypotheses.
The main results to report include:
The mean heights of the plants in the control group, low nitrogen group, and high nitrogen groups were 20.3, 25.1, and 29.6 cm respectively. A one-way ANOVA was applied to calculate the effect of nitrogen fertilizer level on plant height. The results demonstrated statistically significant ( p = .03) height differences between groups.
Next, post-hoc tests were performed to assess the primary and secondary hypotheses. In support of the primary hypothesis, the high nitrogen group plants were significantly taller than the low nitrogen group and the control group plants. Similarly, the results supported the secondary hypothesis: the low nitrogen plants were taller than the control group plants.
These results can be reported in the text or in tables and figures. Use text for highlighting a few key results, but present large sets of numbers in tables, or show relationships between variables with graphs.
You should also include sample calculations in the Results section for complex experiments. For each sample calculation, provide a brief description of what it does and use clear symbols. Present your raw data in the Appendices section and refer to it to highlight any outliers or trends.
The Discussion section will help demonstrate your understanding of the experimental process and your critical thinking skills.
In this section, you can:
Interpreting your results involves clarifying how your results help you answer your main research question. Report whether your results support your hypotheses.
Compare your findings with other research and explain any key differences in findings.
An effective Discussion section will also highlight the strengths and limitations of a study.
When describing limitations, use specific examples. For example, if random error contributed substantially to the measurements in your study, state the particular sources of error (e.g., imprecise apparatus) and explain ways to improve them.
The results support the hypothesis that nitrogen levels affect plant height, with increasing levels producing taller plants. These statistically significant results are taken together with previous research to support the importance of nitrogen as a nutrient for tomato plant growth.
However, unlike previous studies, this study focused on plant height as an indicator of plant growth in the present experiment. Importantly, plant height may not always reflect plant health or fruit yield, so measuring other indicators would have strengthened the study findings.
Another limitation of the study is the plant height measurement technique, as the measuring tape was not suitable for plants with extreme curvature. Future studies may focus on measuring plant height in different ways.
The main strengths of this study were the controls for extraneous variables, such as pH and carbon levels of the soil. All other factors that could affect plant height were tightly controlled to isolate the effects of nitrogen levels, resulting in high internal validity for this study.
Your conclusion should be the final section of your lab report. Here, you’ll summarize the findings of your experiment, with a brief overview of the strengths and limitations, and implications of your study for further research.
Some lab reports may omit a Conclusion section because it overlaps with the Discussion section, but you should check with your instructor before doing so.
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A lab report conveys the aim, methods, results, and conclusions of a scientific experiment . Lab reports are commonly assigned in science, technology, engineering, and mathematics (STEM) fields.
The purpose of a lab report is to demonstrate your understanding of the scientific method with a hands-on lab experiment. Course instructors will often provide you with an experimental design and procedure. Your task is to write up how you actually performed the experiment and evaluate the outcome.
In contrast, a research paper requires you to independently develop an original argument. It involves more in-depth research and interpretation of sources and data.
A lab report is usually shorter than a research paper.
The sections of a lab report can vary between scientific fields and course requirements, but it usually contains the following:
The results chapter or section simply and objectively reports what you found, without speculating on why you found these results. The discussion interprets the meaning of the results, puts them in context, and explains why they matter.
In qualitative research , results and discussion are sometimes combined. But in quantitative research , it’s considered important to separate the objective results from your interpretation of them.
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Ever wondered why scientists across the world are being lauded for discovering the Covid-19 vaccine so early? It’s because every…
Ever wondered why scientists across the world are being lauded for discovering the Covid-19 vaccine so early? It’s because every government knows that vaccines are a result of experimental research design and it takes years of collected data to make one. It takes a lot of time to compare formulas and combinations with an array of possibilities across different age groups, genders and physical conditions. With their efficiency and meticulousness, scientists redefined the meaning of experimental research when they discovered a vaccine in less than a year.
Characteristics of experimental research design, types of experimental research design, advantages and disadvantages of experimental research, examples of experimental research.
Experimental research is a scientific method of conducting research using two variables: independent and dependent. Independent variables can be manipulated to apply to dependent variables and the effect is measured. This measurement usually happens over a significant period of time to establish conditions and conclusions about the relationship between these two variables.
Experimental research is widely implemented in education, psychology, social sciences and physical sciences. Experimental research is based on observation, calculation, comparison and logic. Researchers collect quantitative data and perform statistical analyses of two sets of variables. This method collects necessary data to focus on facts and support sound decisions. It’s a helpful approach when time is a factor in establishing cause-and-effect relationships or when an invariable behavior is seen between the two.
Now that we know the meaning of experimental research, let’s look at its characteristics, types and advantages.
The hypothesis is at the core of an experimental research design. Researchers propose a tentative answer after defining the problem and then test the hypothesis to either confirm or disregard it. Here are a few characteristics of experimental research:
Experimental research is equally effective in non-laboratory settings as it is in labs. It helps in predicting events in an experimental setting. It generalizes variable relationships so that they can be implemented outside the experiment and applied to a wider interest group.
The way a researcher assigns subjects to different groups determines the types of experimental research design .
In a pre-experimental research design, researchers observe a group or various groups to see the effect an independent variable has on the dependent variable to cause change. There is no control group as it is a simple form of experimental research . It’s further divided into three categories:
This design is practical but lacks in certain areas of true experimental criteria.
This design depends on statistical analysis to approve or disregard a hypothesis. It’s an accurate design that can be conducted with or without a pretest on a minimum of two dependent variables assigned randomly. It is further classified into three types:
True experimental research design should have a variable to manipulate, a control group and random distribution.
With experimental research, we can test ideas in a controlled environment before marketing. It acts as the best method to test a theory as it can help in making predictions about a subject and drawing conclusions. Let’s look at some of the advantages that make experimental research useful:
Even though it’s a scientific method, it has a few drawbacks. Here are a few disadvantages of this research method:
Experimental research design is a sophisticated method that investigates relationships or occurrences among people or phenomena under a controlled environment and identifies the conditions responsible for such relationships or occurrences
Experimental research can be used in any industry to anticipate responses, changes, causes and effects. Here are some examples of experimental research :
Experimental research is considered a standard method that uses observations, simulations and surveys to collect data. One of its unique features is the ability to control extraneous variables and their effects. It’s a suitable method for those looking to examine the relationship between cause and effect in a field setting or in a laboratory. Although experimental research design is a scientific approach, research is not entirely a scientific process. As much as managers need to know what is experimental research , they have to apply the correct research method, depending on the aim of the study.
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What this handout is about.
This handout provides a general guide to writing reports about scientific research you’ve performed. In addition to describing the conventional rules about the format and content of a lab report, we’ll also attempt to convey why these rules exist, so you’ll get a clearer, more dependable idea of how to approach this writing situation. Readers of this handout may also find our handout on writing in the sciences useful.
Why do we write research reports.
You did an experiment or study for your science class, and now you have to write it up for your teacher to review. You feel that you understood the background sufficiently, designed and completed the study effectively, obtained useful data, and can use those data to draw conclusions about a scientific process or principle. But how exactly do you write all that? What is your teacher expecting to see?
To take some of the guesswork out of answering these questions, try to think beyond the classroom setting. In fact, you and your teacher are both part of a scientific community, and the people who participate in this community tend to share the same values. As long as you understand and respect these values, your writing will likely meet the expectations of your audience—including your teacher.
So why are you writing this research report? The practical answer is “Because the teacher assigned it,” but that’s classroom thinking. Generally speaking, people investigating some scientific hypothesis have a responsibility to the rest of the scientific world to report their findings, particularly if these findings add to or contradict previous ideas. The people reading such reports have two primary goals:
Your job as a writer, then, is to fulfill these two goals.
Good question. Here is the basic format scientists have designed for research reports:
This format, sometimes called “IMRAD,” may take slightly different shapes depending on the discipline or audience; some ask you to include an abstract or separate section for the hypothesis, or call the Discussion section “Conclusions,” or change the order of the sections (some professional and academic journals require the Methods section to appear last). Overall, however, the IMRAD format was devised to represent a textual version of the scientific method.
The scientific method, you’ll probably recall, involves developing a hypothesis, testing it, and deciding whether your findings support the hypothesis. In essence, the format for a research report in the sciences mirrors the scientific method but fleshes out the process a little. Below, you’ll find a table that shows how each written section fits into the scientific method and what additional information it offers the reader.
states your hypothesis | explains how you derived that hypothesis and how it connects to previous research; gives the purpose of the experiment/study | |
details how you tested your hypothesis | clarifies why you performed your study in that particular way | |
provides raw (i.e., uninterpreted) data collected | (perhaps) expresses the data in table form, as an easy-to-read figure, or as percentages/ratios | |
considers whether the data you obtained support the hypothesis | explores the implications of your finding and judges the potential limitations of your experimental design |
Thinking of your research report as based on the scientific method, but elaborated in the ways described above, may help you to meet your audience’s expectations successfully. We’re going to proceed by explicitly connecting each section of the lab report to the scientific method, then explaining why and how you need to elaborate that section.
Although this handout takes each section in the order in which it should be presented in the final report, you may for practical reasons decide to compose sections in another order. For example, many writers find that composing their Methods and Results before the other sections helps to clarify their idea of the experiment or study as a whole. You might consider using each assignment to practice different approaches to drafting the report, to find the order that works best for you.
The best way to prepare to write the lab report is to make sure that you fully understand everything you need to about the experiment. Obviously, if you don’t quite know what went on during the lab, you’re going to find it difficult to explain the lab satisfactorily to someone else. To make sure you know enough to write the report, complete the following steps:
Once you’ve completed these steps as you perform the experiment, you’ll be in a good position to draft an effective lab report.
How do i write a strong introduction.
For the purposes of this handout, we’ll consider the Introduction to contain four basic elements: the purpose, the scientific literature relevant to the subject, the hypothesis, and the reasons you believed your hypothesis viable. Let’s start by going through each element of the Introduction to clarify what it covers and why it’s important. Then we can formulate a logical organizational strategy for the section.
The inclusion of the purpose (sometimes called the objective) of the experiment often confuses writers. The biggest misconception is that the purpose is the same as the hypothesis. Not quite. We’ll get to hypotheses in a minute, but basically they provide some indication of what you expect the experiment to show. The purpose is broader, and deals more with what you expect to gain through the experiment. In a professional setting, the hypothesis might have something to do with how cells react to a certain kind of genetic manipulation, but the purpose of the experiment is to learn more about potential cancer treatments. Undergraduate reports don’t often have this wide-ranging a goal, but you should still try to maintain the distinction between your hypothesis and your purpose. In a solubility experiment, for example, your hypothesis might talk about the relationship between temperature and the rate of solubility, but the purpose is probably to learn more about some specific scientific principle underlying the process of solubility.
For starters, most people say that you should write out your working hypothesis before you perform the experiment or study. Many beginning science students neglect to do so and find themselves struggling to remember precisely which variables were involved in the process or in what way the researchers felt that they were related. Write your hypothesis down as you develop it—you’ll be glad you did.
As for the form a hypothesis should take, it’s best not to be too fancy or complicated; an inventive style isn’t nearly so important as clarity here. There’s nothing wrong with beginning your hypothesis with the phrase, “It was hypothesized that . . .” Be as specific as you can about the relationship between the different objects of your study. In other words, explain that when term A changes, term B changes in this particular way. Readers of scientific writing are rarely content with the idea that a relationship between two terms exists—they want to know what that relationship entails.
Not a hypothesis:
“It was hypothesized that there is a significant relationship between the temperature of a solvent and the rate at which a solute dissolves.”
Hypothesis:
“It was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases.”
Put more technically, most hypotheses contain both an independent and a dependent variable. The independent variable is what you manipulate to test the reaction; the dependent variable is what changes as a result of your manipulation. In the example above, the independent variable is the temperature of the solvent, and the dependent variable is the rate of solubility. Be sure that your hypothesis includes both variables.
You need to do more than tell your readers what your hypothesis is; you also need to assure them that this hypothesis was reasonable, given the circumstances. In other words, use the Introduction to explain that you didn’t just pluck your hypothesis out of thin air. (If you did pluck it out of thin air, your problems with your report will probably extend beyond using the appropriate format.) If you posit that a particular relationship exists between the independent and the dependent variable, what led you to believe your “guess” might be supported by evidence?
Scientists often refer to this type of justification as “motivating” the hypothesis, in the sense that something propelled them to make that prediction. Often, motivation includes what we already know—or rather, what scientists generally accept as true (see “Background/previous research” below). But you can also motivate your hypothesis by relying on logic or on your own observations. If you’re trying to decide which solutes will dissolve more rapidly in a solvent at increased temperatures, you might remember that some solids are meant to dissolve in hot water (e.g., bouillon cubes) and some are used for a function precisely because they withstand higher temperatures (they make saucepans out of something). Or you can think about whether you’ve noticed sugar dissolving more rapidly in your glass of iced tea or in your cup of coffee. Even such basic, outside-the-lab observations can help you justify your hypothesis as reasonable.
This part of the Introduction demonstrates to the reader your awareness of how you’re building on other scientists’ work. If you think of the scientific community as engaging in a series of conversations about various topics, then you’ll recognize that the relevant background material will alert the reader to which conversation you want to enter.
Generally speaking, authors writing journal articles use the background for slightly different purposes than do students completing assignments. Because readers of academic journals tend to be professionals in the field, authors explain the background in order to permit readers to evaluate the study’s pertinence for their own work. You, on the other hand, write toward a much narrower audience—your peers in the course or your lab instructor—and so you must demonstrate that you understand the context for the (presumably assigned) experiment or study you’ve completed. For example, if your professor has been talking about polarity during lectures, and you’re doing a solubility experiment, you might try to connect the polarity of a solid to its relative solubility in certain solvents. In any event, both professional researchers and undergraduates need to connect the background material overtly to their own work.
Most of the time, writers begin by stating the purpose or objectives of their own work, which establishes for the reader’s benefit the “nature and scope of the problem investigated” (Day 1994). Once you have expressed your purpose, you should then find it easier to move from the general purpose, to relevant material on the subject, to your hypothesis. In abbreviated form, an Introduction section might look like this:
“The purpose of the experiment was to test conventional ideas about solubility in the laboratory [purpose] . . . According to Whitecoat and Labrat (1999), at higher temperatures the molecules of solvents move more quickly . . . We know from the class lecture that molecules moving at higher rates of speed collide with one another more often and thus break down more easily [background material/motivation] . . . Thus, it was hypothesized that as the temperature of a solvent increases, the rate at which a solute will dissolve in that solvent increases [hypothesis].”
Again—these are guidelines, not commandments. Some writers and readers prefer different structures for the Introduction. The one above merely illustrates a common approach to organizing material.
As with any piece of writing, your Methods section will succeed only if it fulfills its readers’ expectations, so you need to be clear in your own mind about the purpose of this section. Let’s review the purpose as we described it above: in this section, you want to describe in detail how you tested the hypothesis you developed and also to clarify the rationale for your procedure. In science, it’s not sufficient merely to design and carry out an experiment. Ultimately, others must be able to verify your findings, so your experiment must be reproducible, to the extent that other researchers can follow the same procedure and obtain the same (or similar) results.
Here’s a real-world example of the importance of reproducibility. In 1989, physicists Stanley Pons and Martin Fleischman announced that they had discovered “cold fusion,” a way of producing excess heat and power without the nuclear radiation that accompanies “hot fusion.” Such a discovery could have great ramifications for the industrial production of energy, so these findings created a great deal of interest. When other scientists tried to duplicate the experiment, however, they didn’t achieve the same results, and as a result many wrote off the conclusions as unjustified (or worse, a hoax). To this day, the viability of cold fusion is debated within the scientific community, even though an increasing number of researchers believe it possible. So when you write your Methods section, keep in mind that you need to describe your experiment well enough to allow others to replicate it exactly.
With these goals in mind, let’s consider how to write an effective Methods section in terms of content, structure, and style.
Sometimes the hardest thing about writing this section isn’t what you should talk about, but what you shouldn’t talk about. Writers often want to include the results of their experiment, because they measured and recorded the results during the course of the experiment. But such data should be reserved for the Results section. In the Methods section, you can write that you recorded the results, or how you recorded the results (e.g., in a table), but you shouldn’t write what the results were—not yet. Here, you’re merely stating exactly how you went about testing your hypothesis. As you draft your Methods section, ask yourself the following questions:
Describe the control in the Methods section. Two things are especially important in writing about the control: identify the control as a control, and explain what you’re controlling for. Here is an example:
“As a control for the temperature change, we placed the same amount of solute in the same amount of solvent, and let the solution stand for five minutes without heating it.”
Organization is especially important in the Methods section of a lab report because readers must understand your experimental procedure completely. Many writers are surprised by the difficulty of conveying what they did during the experiment, since after all they’re only reporting an event, but it’s often tricky to present this information in a coherent way. There’s a fairly standard structure you can use to guide you, and following the conventions for style can help clarify your points.
Increasingly, especially in the social sciences, using first person and active voice is acceptable in scientific reports. Most readers find that this style of writing conveys information more clearly and concisely. This rhetorical choice thus brings two scientific values into conflict: objectivity versus clarity. Since the scientific community hasn’t reached a consensus about which style it prefers, you may want to ask your lab instructor.
Here’s a paradox for you. The Results section is often both the shortest (yay!) and most important (uh-oh!) part of your report. Your Materials and Methods section shows how you obtained the results, and your Discussion section explores the significance of the results, so clearly the Results section forms the backbone of the lab report. This section provides the most critical information about your experiment: the data that allow you to discuss how your hypothesis was or wasn’t supported. But it doesn’t provide anything else, which explains why this section is generally shorter than the others.
Before you write this section, look at all the data you collected to figure out what relates significantly to your hypothesis. You’ll want to highlight this material in your Results section. Resist the urge to include every bit of data you collected, since perhaps not all are relevant. Also, don’t try to draw conclusions about the results—save them for the Discussion section. In this section, you’re reporting facts. Nothing your readers can dispute should appear in the Results section.
Most Results sections feature three distinct parts: text, tables, and figures. Let’s consider each part one at a time.
This should be a short paragraph, generally just a few lines, that describes the results you obtained from your experiment. In a relatively simple experiment, one that doesn’t produce a lot of data for you to repeat, the text can represent the entire Results section. Don’t feel that you need to include lots of extraneous detail to compensate for a short (but effective) text; your readers appreciate discrimination more than your ability to recite facts. In a more complex experiment, you may want to use tables and/or figures to help guide your readers toward the most important information you gathered. In that event, you’ll need to refer to each table or figure directly, where appropriate:
“Table 1 lists the rates of solubility for each substance”
“Solubility increased as the temperature of the solution increased (see Figure 1).”
If you do use tables or figures, make sure that you don’t present the same material in both the text and the tables/figures, since in essence you’ll just repeat yourself, probably annoying your readers with the redundancy of your statements.
Feel free to describe trends that emerge as you examine the data. Although identifying trends requires some judgment on your part and so may not feel like factual reporting, no one can deny that these trends do exist, and so they properly belong in the Results section. Example:
“Heating the solution increased the rate of solubility of polar solids by 45% but had no effect on the rate of solubility in solutions containing non-polar solids.”
This point isn’t debatable—you’re just pointing out what the data show.
As in the Materials and Methods section, you want to refer to your data in the past tense, because the events you recorded have already occurred and have finished occurring. In the example above, note the use of “increased” and “had,” rather than “increases” and “has.” (You don’t know from your experiment that heating always increases the solubility of polar solids, but it did that time.)
You shouldn’t put information in the table that also appears in the text. You also shouldn’t use a table to present irrelevant data, just to show you did collect these data during the experiment. Tables are good for some purposes and situations, but not others, so whether and how you’ll use tables depends upon what you need them to accomplish.
Tables are useful ways to show variation in data, but not to present a great deal of unchanging measurements. If you’re dealing with a scientific phenomenon that occurs only within a certain range of temperatures, for example, you don’t need to use a table to show that the phenomenon didn’t occur at any of the other temperatures. How useful is this table?
As you can probably see, no solubility was observed until the trial temperature reached 50°C, a fact that the text part of the Results section could easily convey. The table could then be limited to what happened at 50°C and higher, thus better illustrating the differences in solubility rates when solubility did occur.
As a rule, try not to use a table to describe any experimental event you can cover in one sentence of text. Here’s an example of an unnecessary table from How to Write and Publish a Scientific Paper , by Robert A. Day:
As Day notes, all the information in this table can be summarized in one sentence: “S. griseus, S. coelicolor, S. everycolor, and S. rainbowenski grew under aerobic conditions, whereas S. nocolor and S. greenicus required anaerobic conditions.” Most readers won’t find the table clearer than that one sentence.
When you do have reason to tabulate material, pay attention to the clarity and readability of the format you use. Here are a few tips:
It’s a little tough to see the trends that the author presumably wants to present in this table. Compare this table, in which the data appear vertically:
The second table shows how putting like elements in a vertical column makes for easier reading. In this case, the like elements are the measurements of length and height, over five trials–not, as in the first table, the length and height measurements for each trial.
1058 |
432 |
7 |
Although tables can be useful ways of showing trends in the results you obtained, figures (i.e., illustrations) can do an even better job of emphasizing such trends. Lab report writers often use graphic representations of the data they collected to provide their readers with a literal picture of how the experiment went.
Remember the circumstances under which you don’t need a table: when you don’t have a great deal of data or when the data you have don’t vary a lot. Under the same conditions, you would probably forgo the figure as well, since the figure would be unlikely to provide your readers with an additional perspective. Scientists really don’t like their time wasted, so they tend not to respond favorably to redundancy.
If you’re trying to decide between using a table and creating a figure to present your material, consider the following a rule of thumb. The strength of a table lies in its ability to supply large amounts of exact data, whereas the strength of a figure is its dramatic illustration of important trends within the experiment. If you feel that your readers won’t get the full impact of the results you obtained just by looking at the numbers, then a figure might be appropriate.
Of course, an undergraduate class may expect you to create a figure for your lab experiment, if only to make sure that you can do so effectively. If this is the case, then don’t worry about whether to use figures or not—concentrate instead on how best to accomplish your task.
Figures can include maps, photographs, pen-and-ink drawings, flow charts, bar graphs, and section graphs (“pie charts”). But the most common figure by far, especially for undergraduates, is the line graph, so we’ll focus on that type in this handout.
At the undergraduate level, you can often draw and label your graphs by hand, provided that the result is clear, legible, and drawn to scale. Computer technology has, however, made creating line graphs a lot easier. Most word-processing software has a number of functions for transferring data into graph form; many scientists have found Microsoft Excel, for example, a helpful tool in graphing results. If you plan on pursuing a career in the sciences, it may be well worth your while to learn to use a similar program.
Computers can’t, however, decide for you how your graph really works; you have to know how to design your graph to meet your readers’ expectations. Here are some of these expectations:
The discussion section is probably the least formalized part of the report, in that you can’t really apply the same structure to every type of experiment. In simple terms, here you tell your readers what to make of the Results you obtained. If you have done the Results part well, your readers should already recognize the trends in the data and have a fairly clear idea of whether your hypothesis was supported. Because the Results can seem so self-explanatory, many students find it difficult to know what material to add in this last section.
Basically, the Discussion contains several parts, in no particular order, but roughly moving from specific (i.e., related to your experiment only) to general (how your findings fit in the larger scientific community). In this section, you will, as a rule, need to:
Let’s look at some dos and don’ts for each of these objectives.
This statement is usually a good way to begin the Discussion, since you can’t effectively speak about the larger scientific value of your study until you’ve figured out the particulars of this experiment. You might begin this part of the Discussion by explicitly stating the relationships or correlations your data indicate between the independent and dependent variables. Then you can show more clearly why you believe your hypothesis was or was not supported. For example, if you tested solubility at various temperatures, you could start this section by noting that the rates of solubility increased as the temperature increased. If your initial hypothesis surmised that temperature change would not affect solubility, you would then say something like,
“The hypothesis that temperature change would not affect solubility was not supported by the data.”
Note: Students tend to view labs as practical tests of undeniable scientific truths. As a result, you may want to say that the hypothesis was “proved” or “disproved” or that it was “correct” or “incorrect.” These terms, however, reflect a degree of certainty that you as a scientist aren’t supposed to have. Remember, you’re testing a theory with a procedure that lasts only a few hours and relies on only a few trials, which severely compromises your ability to be sure about the “truth” you see. Words like “supported,” “indicated,” and “suggested” are more acceptable ways to evaluate your hypothesis.
Also, recognize that saying whether the data supported your hypothesis or not involves making a claim to be defended. As such, you need to show the readers that this claim is warranted by the evidence. Make sure that you’re very explicit about the relationship between the evidence and the conclusions you draw from it. This process is difficult for many writers because we don’t often justify conclusions in our regular lives. For example, you might nudge your friend at a party and whisper, “That guy’s drunk,” and once your friend lays eyes on the person in question, she might readily agree. In a scientific paper, by contrast, you would need to defend your claim more thoroughly by pointing to data such as slurred words, unsteady gait, and the lampshade-as-hat. In addition to pointing out these details, you would also need to show how (according to previous studies) these signs are consistent with inebriation, especially if they occur in conjunction with one another. To put it another way, tell your readers exactly how you got from point A (was the hypothesis supported?) to point B (yes/no).
You need to take these exceptions and divergences into account, so that you qualify your conclusions sufficiently. For obvious reasons, your readers will doubt your authority if you (deliberately or inadvertently) overlook a key piece of data that doesn’t square with your perspective on what occurred. In a more philosophical sense, once you’ve ignored evidence that contradicts your claims, you’ve departed from the scientific method. The urge to “tidy up” the experiment is often strong, but if you give in to it you’re no longer performing good science.
Sometimes after you’ve performed a study or experiment, you realize that some part of the methods you used to test your hypothesis was flawed. In that case, it’s OK to suggest that if you had the chance to conduct your test again, you might change the design in this or that specific way in order to avoid such and such a problem. The key to making this approach work, though, is to be very precise about the weakness in your experiment, why and how you think that weakness might have affected your data, and how you would alter your protocol to eliminate—or limit the effects of—that weakness. Often, inexperienced researchers and writers feel the need to account for “wrong” data (remember, there’s no such animal), and so they speculate wildly about what might have screwed things up. These speculations include such factors as the unusually hot temperature in the room, or the possibility that their lab partners read the meters wrong, or the potentially defective equipment. These explanations are what scientists call “cop-outs,” or “lame”; don’t indicate that the experiment had a weakness unless you’re fairly certain that a) it really occurred and b) you can explain reasonably well how that weakness affected your results.
If, for example, your hypothesis dealt with the changes in solubility at different temperatures, then try to figure out what you can rationally say about the process of solubility more generally. If you’re doing an undergraduate lab, chances are that the lab will connect in some way to the material you’ve been covering either in lecture or in your reading, so you might choose to return to these resources as a way to help you think clearly about the process as a whole.
This part of the Discussion section is another place where you need to make sure that you’re not overreaching. Again, nothing you’ve found in one study would remotely allow you to claim that you now “know” something, or that something isn’t “true,” or that your experiment “confirmed” some principle or other. Hesitate before you go out on a limb—it’s dangerous! Use less absolutely conclusive language, including such words as “suggest,” “indicate,” “correspond,” “possibly,” “challenge,” etc.
We’ve been talking about how to show that you belong in a particular community (such as biologists or anthropologists) by writing within conventions that they recognize and accept. Another is to try to identify a conversation going on among members of that community, and use your work to contribute to that conversation. In a larger philosophical sense, scientists can’t fully understand the value of their research unless they have some sense of the context that provoked and nourished it. That is, you have to recognize what’s new about your project (potentially, anyway) and how it benefits the wider body of scientific knowledge. On a more pragmatic level, especially for undergraduates, connecting your lab work to previous research will demonstrate to the TA that you see the big picture. You have an opportunity, in the Discussion section, to distinguish yourself from the students in your class who aren’t thinking beyond the barest facts of the study. Capitalize on this opportunity by putting your own work in context.
If you’re just beginning to work in the natural sciences (as a first-year biology or chemistry student, say), most likely the work you’ll be doing has already been performed and re-performed to a satisfactory degree. Hence, you could probably point to a similar experiment or study and compare/contrast your results and conclusions. More advanced work may deal with an issue that is somewhat less “resolved,” and so previous research may take the form of an ongoing debate, and you can use your own work to weigh in on that debate. If, for example, researchers are hotly disputing the value of herbal remedies for the common cold, and the results of your study suggest that Echinacea diminishes the symptoms but not the actual presence of the cold, then you might want to take some time in the Discussion section to recapitulate the specifics of the dispute as it relates to Echinacea as an herbal remedy. (Consider that you have probably already written in the Introduction about this debate as background research.)
This information is often the best way to end your Discussion (and, for all intents and purposes, the report). In argumentative writing generally, you want to use your closing words to convey the main point of your writing. This main point can be primarily theoretical (“Now that you understand this information, you’re in a better position to understand this larger issue”) or primarily practical (“You can use this information to take such and such an action”). In either case, the concluding statements help the reader to comprehend the significance of your project and your decision to write about it.
Since a lab report is argumentative—after all, you’re investigating a claim, and judging the legitimacy of that claim by generating and collecting evidence—it’s often a good idea to end your report with the same technique for establishing your main point. If you want to go the theoretical route, you might talk about the consequences your study has for the field or phenomenon you’re investigating. To return to the examples regarding solubility, you could end by reflecting on what your work on solubility as a function of temperature tells us (potentially) about solubility in general. (Some folks consider this type of exploration “pure” as opposed to “applied” science, although these labels can be problematic.) If you want to go the practical route, you could end by speculating about the medical, institutional, or commercial implications of your findings—in other words, answer the question, “What can this study help people to do?” In either case, you’re going to make your readers’ experience more satisfying, by helping them see why they spent their time learning what you had to teach them.
We consulted these works while writing this handout. This is not a comprehensive list of resources on the handout’s topic, and we encourage you to do your own research to find additional publications. Please do not use this list as a model for the format of your own reference list, as it may not match the citation style you are using. For guidance on formatting citations, please see the UNC Libraries citation tutorial . We revise these tips periodically and welcome feedback.
American Psychological Association. 2010. Publication Manual of the American Psychological Association . 6th ed. Washington, DC: American Psychological Association.
Beall, Herbert, and John Trimbur. 2001. A Short Guide to Writing About Chemistry , 2nd ed. New York: Longman.
Blum, Deborah, and Mary Knudson. 1997. A Field Guide for Science Writers: The Official Guide of the National Association of Science Writers . New York: Oxford University Press.
Booth, Wayne C., Gregory G. Colomb, Joseph M. Williams, Joseph Bizup, and William T. FitzGerald. 2016. The Craft of Research , 4th ed. Chicago: University of Chicago Press.
Briscoe, Mary Helen. 1996. Preparing Scientific Illustrations: A Guide to Better Posters, Presentations, and Publications , 2nd ed. New York: Springer-Verlag.
Council of Science Editors. 2014. Scientific Style and Format: The CSE Manual for Authors, Editors, and Publishers , 8th ed. Chicago & London: University of Chicago Press.
Davis, Martha. 2012. Scientific Papers and Presentations , 3rd ed. London: Academic Press.
Day, Robert A. 1994. How to Write and Publish a Scientific Paper , 4th ed. Phoenix: Oryx Press.
Porush, David. 1995. A Short Guide to Writing About Science . New York: Longman.
Williams, Joseph, and Joseph Bizup. 2017. Style: Lessons in Clarity and Grace , 12th ed. Boston: Pearson.
You may reproduce it for non-commercial use if you use the entire handout and attribute the source: The Writing Center, University of North Carolina at Chapel Hill
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This section describes an organizational structure commonly used to report experimental research in many scientific disciplines, the IMRAD format: I ntroduction, M ethods, R esults, And D iscussion.
Although most scientific reports use the IMRAD format, there are some exceptions.
This format is usually not used in reports describing other kinds of research, such as field or case studies, in which headings are more likely to differ according to discipline. Although the main headings are standard for many scientific fields, details may vary; check with your instructor, or, if submitting an article to a journal, refer to the instructions to authors.
Titles should.
The Relationship of Luteinizing Hormone to Obesity in the Zucker Rat
An Investigation of Hormone Secretion and Weight in Rats Fat Rats: Are Their Hormones Different?
The guidelines below address issues to consider when writing an abstract.
Guidelines for effective scientific report introductions.
Below are some questions to consider for effective methods sections in scientific reports.
(May be subheaded as Materials)
(May be subheaded as Methods or Procedures)
The section below offers some questions asked for effective results sections in scientific reports.
For each experiment or procedure:
The table below offers some questions effective discussion sections in scientific reports address.
For each major result:
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Here are some tips for writing lab reports! While lab reports are similar in structure and content to research articles published in scientific journals, they have a different purpose and audience, which will shape how you write them. The purpose of your lab report is to share the importance, analysis, and scope of your research. Your audience is your professor, instructor, or peers. While you probably won't be submitting your report to a journal for peer-review, it is still a good idea to adhere to the conventions and guidelines specified by your instructor, because writing these reports is really good practice for any science writing you may go on to do in your career!
"The research report is more than a narrative; it is a careful argument. The authors of a research report find themselves in the position of building a case for their research, not simply recounting actions and observation"
Penrose, A. M., & Katz, S. B. (2001). Writing in the sciences : exploring conventions of scientific discourse / Ann M. Penrose, Steven B. Katz . Pearson Custom Pub. Pp. 33
Avoid first person - It is best to use a passive, third person voice when describing your experiment and results.
Tenses -
Species - All species should be referred to in their full Latin name, in italics
IMAGES
VIDEO
COMMENTS
Step 1: Define your variables. You should begin with a specific research question. We will work with two research question examples, one from health sciences and one from ecology: Example question 1: Phone use and sleep. You want to know how phone use before bedtime affects sleep patterns.
The classic experimental design definition is: "The methods used to collect data in experimental studies.". There are three primary types of experimental design: The way you classify research subjects based on conditions or groups determines the type of research design you should use. 01. Pre-Experimental Design.
Experimental research serves as a fundamental scientific method aimed at unraveling. cause-and-effect relationships between variables across various disciplines. This. paper delineates the key ...
An experimental design is a detailed plan for collecting and using data to identify causal relationships. Through careful planning, the design of experiments allows your data collection efforts to have a reasonable chance of detecting effects and testing hypotheses that answer your research questions. An experiment is a data collection ...
The three main types of experimental research design are: 1. Pre-experimental research. A pre-experimental research study is an observational approach to performing an experiment. It's the most basic style of experimental research. Free experimental research can occur in one of these design structures: One-shot case study research design: In ...
Experimental research is a systematic and scientific approach in which the researcher manipulates one or more independent variables and observes the effect on a dependent variable while controlling for extraneous variables. This method allows for the establishment of cause-and-effect relationships between variables.
Experimental reports (also known as "lab reports") are reports of empirical research conducted by their authors. You should think of an experimental report as a "story" of your research in which you lead your readers through your experiment. As you are telling this story, you are crafting an argument about both the validity and reliability of ...
Experimental Design. Experimental design is a process of planning and conducting scientific experiments to investigate a hypothesis or research question. It involves carefully designing an experiment that can test the hypothesis, and controlling for other variables that may influence the results. Experimental design typically includes ...
Experimental research is best suited for explanatory research—rather than for descriptive or exploratory research—where the goal of the study is to examine cause-effect relationships. It also works well for research that involves a relatively limited and well-defined set of independent variables that can either be manipulated or controlled.
Step 1: Define your variables. You should begin with a specific research question. We will work with two research question examples, one from health sciences and one from ecology: Example question 1: Phone use and sleep. You want to know how phone use before bedtime affects sleep patterns.
Study, experimental, or research design is the backbone of good research. It directs the experiment by orchestrating data collection, defines the statistical analysis of the resultant data, and guides the interpretation of the results. When properly described in the written report of the experiment, it serves as a road map to readers, 1 helping ...
An example of experimental research in marketing: The ideal goal of a marketing product, advertisement, or campaign is to attract attention and create positive emotions in the target audience. Marketers can focus on different elements in different campaigns, change the packaging/outline, and have a different approach.
Definition: Research Report is a written document that presents the results of a research project or study, including the research question, methodology, results, and conclusions, in a clear and objective manner. ... Experimental Report. An experimental report documents the results of a scientific experiment, including the hypothesis, methods ...
Collect the data by using suitable data collection according to your experiment's requirement, such as observations, case studies, surveys, interviews, questionnaires, etc. Analyse the obtained information. Step 8. Present and Conclude the Findings of the Study. Write the report of your research.
Experimental science is the queen of sciences and the goal of all speculation. Roger Bacon (1214-1294) Download chapter PDF. Experiments are part of the scientific method that helps to decide the fate of two or more competing hypotheses or explanations on a phenomenon. The term 'experiment' arises from Latin, Experiri, which means, 'to ...
Experimental research design is a framework of protocols and procedures created to conduct experimental research with a scientific approach using two sets of variables. Herein, the first set of variables acts as a constant, used to measure the differences of the second set. The best example of experimental research methods is quantitative research.
Three types of experimental designs are commonly used: 1. Independent Measures. Independent measures design, also known as between-groups, is an experimental design where different participants are used in each condition of the independent variable. This means that each condition of the experiment includes a different group of participants.
Experimental research design is centrally concerned with constructing research that is high in causal (internal) validity. Randomized experimental designs provide the highest levels of causal validity. Quasi-experimental designs have a number of potential threats to their causal validity. Yet, new quasi-experimental designs adopted from fields ...
The pre-experimental research design is further divided into three types. One-shot Case Study Research Design. In this type of experimental study, only one dependent group or variable is considered. The study is carried out after some treatment which was presumed to cause change, making it a posttest study.
Introduction. Your lab report introduction should set the scene for your experiment. One way to write your introduction is with a funnel (an inverted triangle) structure: Start with the broad, general research topic. Narrow your topic down your specific study focus. End with a clear research question.
Experimental research is widely implemented in education, psychology, social sciences and physical sciences. Experimental research is based on observation, calculation, comparison and logic. Researchers collect quantitative data and perform statistical analyses of two sets of variables. This method collects necessary data to focus on facts and ...
What this handout is about. This handout provides a general guide to writing reports about scientific research you've performed. In addition to describing the conventional rules about the format and content of a lab report, we'll also attempt to convey why these rules exist, so you'll get a clearer, more dependable idea of how to approach ...
This section describes an organizational structure commonly used to report experimental research in many scientific disciplines, the IMRAD format: Introduction, Methods, Results, And Discussion. Although the main headings are standard for many scientific fields, details may vary; check with your instructor, or, if submitting an article to a journal, refer to the instructions to authors.…
Avoid first person - It is best to use a passive, third person voice when describing your experiment and results. For example - "The sample was analyzed.The results were positive." Tenses - Present tense: Use to describe accepted scientific information. Past tense: Use when discussing your research and findings. Future: Use when discussing how your research applies to future scientific endeavors.
Research Paper. Experimental investigation of metakaolin ingredients on bonding of steel fibers to cement in paste of steel fiber concrete under sulfate and sulfate-chloride attack ... (≤75 μm) were used (MK mean particle size was 9.7 μm) and 15.0 % of MK (60.0 g), by weight of total mix, was considered as a substitution for cement in the ...