lab experiment hypothesis

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How to Write a Lab Report – with Example/Template

April 11, 2024

Perhaps you’re in the midst of your challenging AP chemistry class in high school, or perhaps college you’re enrolled in biology , chemistry , or physics at university. At some point, you will likely be asked to write a lab report. Sometimes, your teacher or professor will give you specific instructions for how to format and write your lab report, and if so, use that. In case you’re left to your own devices, here are some guidelines you might find useful. Continue reading for the main elements of a lab report, followed by a detailed description of the more writing-heavy parts (with a lab report example/lab report template). Lastly, we’ve included an outline that can help get you started.

What is a lab report?

A lab report is an overview of your experiment. Essentially, it explains what you did in the experiment and how it went. Most lab reports end up being 5-10 pages long (graphs or other images included), though the length depends on the experiment. Here are some brief explanations of the essential parts of a lab report:

Title : The title says, in the most straightforward way possible, what you did in the experiment. Often, the title looks something like, “Effects of ____ on _____.” Sometimes, a lab report also requires a title page, which includes your name (and the names of any lab partners), your instructor’s name, and the date of the experiment.

Abstract : This is a short description of key findings of the experiment so that a potential reader could get an idea of the experiment before even beginning.

Introduction : This is comprised of one or several paragraphs summarizing the purpose of the lab. The introduction usually includes the hypothesis, as well as some background information.

Lab Report Example (Continued)

Materials : Perhaps the simplest part of your lab report, this is where you list everything needed for the completion of your experiment.

Methods : This is where you describe your experimental procedure. The section provides necessary information for someone who would want to replicate your study. In paragraph form, write out your methods in chronological order, though avoid excessive detail.

Data : Here, you should document what happened in the experiment, step-by-step. This section often includes graphs and tables with data, as well as descriptions of patterns and trends. You do not need to interpret all of the data in this section, but you can describe trends or patterns, and state which findings are interesting and/or significant.

Discussion of results : This is the overview of your findings from the experiment, with an explanation of how they pertain to your hypothesis, as well as any anomalies or errors.

Conclusion : Your conclusion will sum up the results of your experiment, as well as their significance. Sometimes, conclusions also suggest future studies.

Sources : Often in APA style , you should list all texts that helped you with your experiment. Make sure to include course readings, outside sources, and other experiments that you may have used to design your own.

How to write the abstract

The abstract is the experiment stated “in a nutshell”: the procedure, results, and a few key words. The purpose of the academic abstract is to help a potential reader get an idea of the experiment so they can decide whether to read the full paper. So, make sure your abstract is as clear and direct as possible, and under 200 words (though word count varies).

When writing an abstract for a scientific lab report, we recommend covering the following points:

• Background : Why was this experiment conducted?
• Objectives : What problem is being addressed by this experiment?
• Methods : How was the study designed and conducted?
• Results : What results were found and what do they mean?
• Conclusion : Were the results expected? Is this problem better understood now than before? If so, how?

How to write the introduction

The introduction is another summary, of sorts, so it could be easy to confuse the introduction with the abstract. While the abstract tends to be around 200 words summarizing the entire study, the introduction can be longer if necessary, covering background information on the study, what you aim to accomplish, and your hypothesis. Unlike the abstract (or the conclusion), the introduction does not need to state the results of the experiment.

Here is a possible order with which you can organize your lab report introduction:

• Intro of the intro : Plainly state what your study is doing.
• Background : Provide a brief overview of the topic being studied. This could include key terms and definitions. This should not be an extensive literature review, but rather, a window into the most relevant topics a reader would need to understand in order to understand your research.
• Importance : Now, what are the gaps in existing research? Given the background you just provided, what questions do you still have that led you to conduct this experiment? Are you clarifying conflicting results? Are you undertaking a new area of research altogether?
• Prediction: The plants placed by the window will grow faster than plants placed in the dark corner.
• Hypothesis: Basil plants placed in direct sunlight for 2 hours per day grow at a higher rate than basil plants placed in direct sunlight for 30 minutes per day.
• How you test your hypothesis : This is an opportunity to briefly state how you go about your experiment, but this is not the time to get into specific details about your methods (save this for your results section). Keep this part down to one sentence, and voila! You have your introduction.

How to write a discussion section

Here, we’re skipping ahead to the next writing-heavy section, which will directly follow the numeric data of your experiment. The discussion includes any calculations and interpretations based on this data. In other words, it says, “Now that we have the data, why should we care?”  This section asks, how does this data sit in relation to the hypothesis? Does it prove your hypothesis or disprove it? The discussion is also a good place to mention any mistakes that were made during the experiment, and ways you would improve the experiment if you were to repeat it. Like the other written sections, it should be as concise as possible.

Here is a list of points to cover in your lab report discussion:

• Weaker statement: These findings prove that basil plants grow more quickly in the sunlight.
• Stronger statement: These findings support the hypothesis that basil plants placed in direct sunlight grow at a higher rate than basil plants given less direct sunlight.
• Factors influencing results : This is also an opportunity to mention any anomalies, errors, or inconsistencies in your data. Perhaps when you tested the first round of basil plants, the days were sunnier than the others. Perhaps one of the basil pots broke mid-experiment so it needed to be replanted, which affected your results. If you were to repeat the study, how would you change it so that the results were more consistent?
• Implications : How do your results contribute to existing research? Here, refer back to the gaps in research that you mentioned in your introduction. Do these results fill these gaps as you hoped?
• Questions for future research : Based on this, how might your results contribute to future research? What are the next steps, or the next experiments on this topic? Make sure this does not become too broad—keep it to the scope of this project.

How to write a lab report conclusion

This is your opportunity to briefly remind the reader of your findings and finish strong. Your conclusion should be especially concise (avoid going into detail on findings or introducing new information).

Here are elements to include as you write your conclusion, in about 1-2 sentences each:

• Restate your goals : What was the main question of your experiment? Refer back to your introduction—similar language is okay.
• Restate your methods : In a sentence or so, how did you go about your experiment?
• Key findings : Briefly summarize your main results, but avoid going into detail.
• Limitations : What about your experiment was less-than-ideal, and how could you improve upon the experiment in future studies?
• Significance and future research : Why is your research important? What are the logical next-steps for studying this topic?

Template for beginning your lab report

Here is a compiled outline from the bullet points in these sections above, with some examples based on the (overly-simplistic) basil growth experiment. Hopefully this will be useful as you begin your lab report.

1) Title (ex: Effects of Sunlight on Basil Plant Growth )

2) Abstract (approx. 200 words)

• Background ( This experiment looks at… )
• Objectives ( It aims to contribute to research on…)
• Methods ( It does so through a process of…. )
• Results (Findings supported the hypothesis that… )
• Conclusion (These results contribute to a wider understanding about…)

3) Introduction (approx. 1-2 paragraphs)

• Intro ( This experiment looks at… )
• Background ( Past studies on basil plant growth and sunlight have found…)
• Importance ( This experiment will contribute to these past studies by…)
• Hypothesis ( Basil plants placed in direct sunlight for 2 hours per day grow at a higher rate than basil plants placed in direct sunlight for 30 minutes per day.)
• How you will test your hypothesis ( This hypothesis will be tested by a process of…)

4) Materials (list form) (ex: pots, soil, seeds, tables/stands, water, light source )

5) Methods (approx. 1-2 paragraphs) (ex: 10 basil plants were measured throughout a span of…)

6) Data (brief description and figures) (ex: These charts demonstrate a pattern that the basil plants placed in direct sunlight…)

7) Discussion (approx. 2-3 paragraphs)

• Support or reject hypothesis ( These findings support the hypothesis that basil plants placed in direct sunlight grow at a higher rate than basil plants given less direct sunlight.)
• Factors that influenced your results ( Outside factors that could have altered the results include…)
• Implications ( These results contribute to current research on basil plant growth and sunlight because…)
• Questions for further research ( Next steps for this research could include…)
• Restate your goals ( In summary, the goal of this experiment was to measure…)
• Restate your methods ( This hypothesis was tested by…)
• Key findings ( The findings supported the hypothesis because…)
• Limitations ( Although, certain elements were overlooked, including…)
• Significance and future research ( This experiment presents possibilities of future research contributions, such as…)
• Sources (approx. 1 page, usually in APA style)

Final thoughts – Lab Report Example

Hopefully, these descriptions have helped as you write your next lab report. Remember that different instructors may have different preferences for structure and format, so make sure to double-check when you receive your assignment. All in all, make sure to keep your scientific lab report concise, focused, honest, and organized. Good luck!

For more reading on coursework success, check out the following articles:

• How to Write the AP Lang Argument Essay (With Example)
• How to Write the AP Lang Rhetorical Analysis Essay (With Example)
• 49 Most Interesting Biology Research Topics
• 50 Best Environmental Science Research Topics
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Writing the Experimental Report: Overview, Introductions, and Literature Reviews

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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 your research, what your results mean, and how they fit into other previous work.

These next two sections provide an overview of the experimental report in APA format. Always check with your instructor, advisor, or journal editor for specific formatting guidelines.

General-specific-general format

Experimental reports follow a general to specific to general pattern. Your report will start off broadly in your introduction and discussion of the literature; the report narrows as it leads up to your specific hypotheses, methods, and results. Your discussion transitions from talking about your specific results to more general ramifications, future work, and trends relating to your research.

Experimental reports in APA format have a title page. Title page formatting is as follows:

• A running head and page number in the upper right corner (right aligned)
• A definition of running head in IN ALL CAPS below the running head (left aligned)
• Vertically and horizontally centered paper title, followed by author and affiliation

Please see our sample APA title page .

Crafting your story

Before you begin to write, carefully consider your purpose in writing: what is it that you discovered, would like to share, or would like to argue? You can see report writing as crafting a story about your research and your findings. Consider the following.

• What is the story you would like to tell?
• What literature best speaks to that story?
• How do your results tell the story?
• How can you discuss the story in broad terms?

During each section of your paper, you should be focusing on your story. Consider how each sentence, each paragraph, and each section contributes to your overall purpose in writing. Here is a description of one student's process.

Briel is writing an experimental report on her results from her experimental psychology lab class. She was interested in looking at the role gender plays in persuading individuals to take financial risks. After her data analysis, she finds that men are more easily persuaded by women to take financial risks and that men are generally willing to take more financial risks.

When Briel begins to write, she focuses her introduction on financial risk taking and gender, focusing on male behaviors. She then presents relevant literature on financial risk taking and gender that help illuminate her own study, but also help demonstrate the need for her own work. Her introduction ends with a study overview that directly leads from the literature review. Because she has already broadly introduced her study through her introduction and literature review, her readers can anticipate where she is going when she gets to her study overview. Her methods and results continue that story. Finally, her discussion concludes that story, discussing her findings, implications of her work, and the need for more research in the area of gender and financial risk taking.

The abstract gives a concise summary of the contents of the report.

• Abstracts should be brief (about 100 words)
• Abstracts should be self-contained and provide a complete picture of what the study is about
• Abstracts should be organized just like your experimental report—introduction, literature review, methods, results and discussion
• Abstracts should be written last during your drafting stage

Introduction

The introduction in an experimental article should follow a general to specific pattern, where you first introduce the problem generally and then provide a short overview of your own study. The introduction includes three parts: opening statements, literature review, and study overview.

Opening statements: Define the problem broadly in plain English and then lead into the literature review (this is the "general" part of the introduction). Your opening statements should already be setting the stage for the story you are going to tell.

Literature review: Discusses literature (previous studies) relevant to your current study in a concise manner. Keep your story in mind as you organize your lit review and as you choose what literature to include. The following are tips when writing your literature review.

• You should discuss studies that are directly related to your problem at hand and that logically lead to your own hypotheses.
• You do not need to provide a complete historical overview nor provide literature that is peripheral to your own study.
• Studies should be presented based on themes or concepts relevant to your research, not in a chronological format.
• You should also consider what gap in the literature your own research fills. What hasn't been examined? What does your work do that others have not?

Study overview: The literature review should lead directly into the last section of the introduction—your study overview. Your short overview should provide your hypotheses and briefly describe your method. The study overview functions as a transition to your methods section.

You should always give good, descriptive names to your hypotheses that you use consistently throughout your study. When you number hypotheses, readers must go back to your introduction to find them, which makes your piece more difficult to read. Using descriptive names reminds readers what your hypotheses were and allows for better overall flow.

In our example above, Briel had three different hypotheses based on previous literature. Her first hypothesis, the "masculine risk-taking hypothesis" was that men would be more willing to take financial risks overall. She clearly named her hypothesis in the study overview, and then referred back to it in her results and discussion sections.

Thais and Sanford (2000) recommend the following organization for introductions.

• Provide an introduction to your topic
• Provide a very concise overview of the literature
• State your hypotheses and how they connect to the literature
• Provide an overview of the methods for investigation used in your research

Bem (2006) provides the following rules of thumb for writing introductions.

• Write in plain English
• Take the time and space to introduce readers to your problem step-by-step; do not plunge them into the middle of the problem without an introduction
• Use examples to illustrate difficult or unfamiliar theories or concepts. The more complicated the concept or theory, the more important it is to have clear examples
• Open with a discussion about people and their behavior, not about psychologists and their research

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Step-by-Step Guide: How to Craft a Strong Research Hypothesis

• 4 minute read
• 386.6K views

Table of Contents

A research hypothesis is a concise statement about the expected result of an experiment or project. In many ways, a research hypothesis represents the starting point for a scientific endeavor, as it establishes a tentative assumption that is eventually substantiated or falsified, ultimately improving our certainty about the subject investigated.   

To help you with this and ease the process, in this article, we discuss the purpose of research hypotheses and list the most essential qualities of a compelling hypothesis. Let’s find out!  

How to Craft a Research Hypothesis  

Crafting a research hypothesis begins with a comprehensive literature review to identify a knowledge gap in your field. Once you find a question or problem, come up with a possible answer or explanation, which becomes your hypothesis. Now think about the specific methods of experimentation that can prove or disprove the hypothesis, which ultimately lead to the results of the study.   

Enlisted below are some standard formats in which you can formulate a hypothesis¹ :  

• A hypothesis can use the if/then format when it seeks to explore the correlation between two variables in a study primarily.  

Example: If administered drug X, then patients will experience reduced fatigue from cancer treatment.  

• A hypothesis can adopt when X/then Y format when it primarily aims to expose a connection between two variables  

Example: When workers spend a significant portion of their waking hours in sedentary work , then they experience a greater frequency of digestive problems.  

• A hypothesis can also take the form of a direct statement.  

Example: Drug X and drug Y reduce the risk of cognitive decline through the same chemical pathways  

What are the Features of an Effective Hypothesis?  

Hypotheses in research need to satisfy specific criteria to be considered scientifically rigorous. Here are the most notable qualities of a strong hypothesis:  

• Testability: Ensure the hypothesis allows you to work towards observable and testable results.  
• Brevity and objectivity: Present your hypothesis as a brief statement and avoid wordiness.  
• Clarity and Relevance: The hypothesis should reflect a clear idea of what we know and what we expect to find out about a phenomenon and address the significant knowledge gap relevant to a field of study.   

Understanding Null and Alternative Hypotheses in Research  

There are two types of hypotheses used commonly in research that aid statistical analyses. These are known as the null hypothesis and the alternative hypothesis . A null hypothesis is a statement assumed to be factual in the initial phase of the study.   

For example, if a researcher is testing the efficacy of a new drug, then the null hypothesis will posit that the drug has no benefits compared to an inactive control or placebo . Suppose the data collected through a drug trial leads a researcher to reject the null hypothesis. In that case, it is considered to substantiate the alternative hypothesis in the above example, that the new drug provides benefits compared to the placebo.  

Let’s take a closer look at the null hypothesis and alternative hypothesis with two more examples:  

Null Hypothesis:  

The rate of decline in the number of species in habitat X in the last year is the same as in the last 100 years when controlled for all factors except the recent wildfires.  

In the next experiment, the researcher will experimentally reject this null hypothesis in order to confirm the following alternative hypothesis :  

The rate of decline in the number of species in habitat X in the last year is different from the rate of decline in the last 100 years when controlled for all factors other than the recent wildfires.  

In the pair of null and alternative hypotheses stated above, a statistical comparison of the rate of species decline over a century and the preceding year will help the research experimentally test the null hypothesis, helping to draw scientifically valid conclusions about two factors—wildfires and species decline.   

We also recommend that researchers pay attention to contextual echoes and connections when writing research hypotheses. Research hypotheses are often closely linked to the introduction ² , such as the context of the study, and can similarly influence the reader’s judgment of the relevance and validity of the research hypothesis.  

Seasoned experts, such as professionals at Elsevier Language Services, guide authors on how to best embed a hypothesis within an article so that it communicates relevance and credibility. Contact us if you want help in ensuring readers find your hypothesis robust and unbiased.  

References  

• Hypotheses – The University Writing Center. (n.d.). https://writingcenter.tamu.edu/writing-speaking-guides/hypotheses  
• Shaping the research question and hypothesis. (n.d.). Students. https://students.unimelb.edu.au/academic-skills/graduate-research-services/writing-thesis-sections-part-2/shaping-the-research-question-and-hypothesis  

Systematic Literature Review or Literature Review?

How to Write an Effective Problem Statement for Your Research Paper

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• How to Write a Strong Hypothesis | Guide & Examples

How to Write a Strong Hypothesis | Guide & Examples

Published on 6 May 2022 by Shona McCombes .

A hypothesis is a statement that can be tested by scientific research. If you want to test a relationship between two or more variables, you need to write hypotheses before you start your experiment or data collection.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, frequently asked questions about writing hypotheses.

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

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

Variables in hypotheses

Hypotheses propose a relationship between two or more variables . An independent variable is something the researcher changes or controls. A dependent variable is something the researcher observes and measures.

In this example, the independent variable is exposure to the sun – the assumed cause . The dependent variable is the level of happiness – the assumed effect .

Prevent plagiarism, run a free check.

Step 1: ask a question.

Writing a hypothesis begins with a research question that you want to answer. The question should be focused, specific, and researchable within the constraints of your project.

Step 2: Do some preliminary research

Your initial answer to the question should be based on what is already known about the topic. Look for theories and previous studies to help you form educated assumptions about what your research will find.

At this stage, you might construct a conceptual framework to identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalise more complex constructs.

Step 3: Formulate your hypothesis

Now you should have some idea of what you expect to find. Write your initial answer to the question in a clear, concise sentence.

Step 4: Refine your hypothesis

You need to make sure your hypothesis is specific and testable. There are various ways of phrasing a hypothesis, but all the terms you use should have clear definitions, and the hypothesis should contain:

• The relevant variables
• The specific group being studied
• The predicted outcome of the experiment or analysis

Step 5: Phrase your hypothesis in three ways

To identify the variables, you can write a simple prediction in if … then form. The first part of the sentence states the independent variable and the second part states the dependent variable.

In academic research, hypotheses are more commonly phrased in terms of correlations or effects, where you directly state the predicted relationship between variables.

If you are comparing two groups, the hypothesis can state what difference you expect to find between them.

Step 6. Write a null hypothesis

If your research involves statistical hypothesis testing , you will also have to write a null hypothesis. The null hypothesis is the default position that there is no association between the variables. The null hypothesis is written as H 0 , while the alternative hypothesis is H 1 or H a .

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

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

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

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

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How the Experimental Method Works in Psychology

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The Experimental Process

Types of experiments, potential pitfalls of the experimental method.

The experimental method is a type of research procedure that involves manipulating variables to determine if there is a cause-and-effect relationship. The results obtained through the experimental method are useful but do not prove with 100% certainty that a singular cause always creates a specific effect. Instead, they show the probability that a cause will or will not lead to a particular effect.

At a Glance

While there are many different research techniques available, the experimental method allows researchers to look at cause-and-effect relationships. Using the experimental method, researchers randomly assign participants to a control or experimental group and manipulate levels of an independent variable. If changes in the independent variable lead to changes in the dependent variable, it indicates there is likely a causal relationship between them.

What Is the Experimental Method in Psychology?

The experimental method involves manipulating one variable to determine if this causes changes in another variable. This method relies on controlled research methods and random assignment of study subjects to test a hypothesis.

For example, researchers may want to learn how different visual patterns may impact our perception. Or they might wonder whether certain actions can improve memory . Experiments are conducted on many behavioral topics, including:

The scientific method forms the basis of the experimental method. This is a process used to determine the relationship between two variables—in this case, to explain human behavior .

Positivism is also important in the experimental method. It refers to factual knowledge that is obtained through observation, which is considered to be trustworthy.

When using the experimental method, researchers first identify and define key variables. Then they formulate a hypothesis, manipulate the variables, and collect data on the results. Unrelated or irrelevant variables are carefully controlled to minimize the potential impact on the experiment outcome.

History of the Experimental Method

The idea of using experiments to better understand human psychology began toward the end of the nineteenth century. Wilhelm Wundt established the first formal laboratory in 1879.

Wundt is often called the father of experimental psychology. He believed that experiments could help explain how psychology works, and used this approach to study consciousness .

Wundt coined the term "physiological psychology." This is a hybrid of physiology and psychology, or how the body affects the brain.

Other early contributors to the development and evolution of experimental psychology as we know it today include:

• Gustav Fechner (1801-1887), who helped develop procedures for measuring sensations according to the size of the stimulus
• Hermann von Helmholtz (1821-1894), who analyzed philosophical assumptions through research in an attempt to arrive at scientific conclusions
• Franz Brentano (1838-1917), who called for a combination of first-person and third-person research methods when studying psychology
• Georg Elias Müller (1850-1934), who performed an early experiment on attitude which involved the sensory discrimination of weights and revealed how anticipation can affect this discrimination

Key Terms to Know

To understand how the experimental method works, it is important to know some key terms.

Dependent Variable

The dependent variable is the effect that the experimenter is measuring. If a researcher was investigating how sleep influences test scores, for example, the test scores would be the dependent variable.

Independent Variable

The independent variable is the variable that the experimenter manipulates. In the previous example, the amount of sleep an individual gets would be the independent variable.

A hypothesis is a tentative statement or a guess about the possible relationship between two or more variables. In looking at how sleep influences test scores, the researcher might hypothesize that people who get more sleep will perform better on a math test the following day. The purpose of the experiment, then, is to either support or reject this hypothesis.

Operational definitions are necessary when performing an experiment. When we say that something is an independent or dependent variable, we must have a very clear and specific definition of the meaning and scope of that variable.

Extraneous Variables

Extraneous variables are other variables that may also affect the outcome of an experiment. Types of extraneous variables include participant variables, situational variables, demand characteristics, and experimenter effects. In some cases, researchers can take steps to control for extraneous variables.

Demand Characteristics

Demand characteristics are subtle hints that indicate what an experimenter is hoping to find in a psychology experiment. This can sometimes cause participants to alter their behavior, which can affect the results of the experiment.

Intervening Variables

Intervening variables are factors that can affect the relationship between two other variables. 

Confounding Variables

Confounding variables are variables that can affect the dependent variable, but that experimenters cannot control for. Confounding variables can make it difficult to determine if the effect was due to changes in the independent variable or if the confounding variable may have played a role.

Psychologists, like other scientists, use the scientific method when conducting an experiment. The scientific method is a set of procedures and principles that guide how scientists develop research questions, collect data, and come to conclusions.

The five basic steps of the experimental process are:

• Identifying a problem to study
• Devising the research protocol
• Conducting the experiment
• Analyzing the data collected
• Sharing the findings (usually in writing or via presentation)

Most psychology students are expected to use the experimental method at some point in their academic careers. Learning how to conduct an experiment is important to understanding how psychologists prove and disprove theories in this field.

There are a few different types of experiments that researchers might use when studying psychology. Each has pros and cons depending on the participants being studied, the hypothesis, and the resources available to conduct the research.

Lab Experiments

Lab experiments are common in psychology because they allow experimenters more control over the variables. These experiments can also be easier for other researchers to replicate. The drawback of this research type is that what takes place in a lab is not always what takes place in the real world.

Field Experiments

Sometimes researchers opt to conduct their experiments in the field. For example, a social psychologist interested in researching prosocial behavior might have a person pretend to faint and observe how long it takes onlookers to respond.

This type of experiment can be a great way to see behavioral responses in realistic settings. But it is more difficult for researchers to control the many variables existing in these settings that could potentially influence the experiment's results.

Quasi-Experiments

While lab experiments are known as true experiments, researchers can also utilize a quasi-experiment. Quasi-experiments are often referred to as natural experiments because the researchers do not have true control over the independent variable.

A researcher looking at personality differences and birth order, for example, is not able to manipulate the independent variable in the situation (personality traits). Participants also cannot be randomly assigned because they naturally fall into pre-existing groups based on their birth order.

So why would a researcher use a quasi-experiment? This is a good choice in situations where scientists are interested in studying phenomena in natural, real-world settings. It's also beneficial if there are limits on research funds or time.

Field experiments can be either quasi-experiments or true experiments.

Examples of the Experimental Method in Use

The experimental method can provide insight into human thoughts and behaviors, Researchers use experiments to study many aspects of psychology.

A 2019 study investigated whether splitting attention between electronic devices and classroom lectures had an effect on college students' learning abilities. It found that dividing attention between these two mediums did not affect lecture comprehension. However, it did impact long-term retention of the lecture information, which affected students' exam performance.

An experiment used participants' eye movements and electroencephalogram (EEG) data to better understand cognitive processing differences between experts and novices. It found that experts had higher power in their theta brain waves than novices, suggesting that they also had a higher cognitive load.

A study looked at whether chatting online with a computer via a chatbot changed the positive effects of emotional disclosure often received when talking with an actual human. It found that the effects were the same in both cases.

One experimental study evaluated whether exercise timing impacts information recall. It found that engaging in exercise prior to performing a memory task helped improve participants' short-term memory abilities.

Sometimes researchers use the experimental method to get a bigger-picture view of psychological behaviors and impacts. For example, one 2018 study examined several lab experiments to learn more about the impact of various environmental factors on building occupant perceptions.

A 2020 study set out to determine the role that sensation-seeking plays in political violence. This research found that sensation-seeking individuals have a higher propensity for engaging in political violence. It also found that providing access to a more peaceful, yet still exciting political group helps reduce this effect.

While the experimental method can be a valuable tool for learning more about psychology and its impacts, it also comes with a few pitfalls.

Experiments may produce artificial results, which are difficult to apply to real-world situations. Similarly, researcher bias can impact the data collected. Results may not be able to be reproduced, meaning the results have low reliability .

Since humans are unpredictable and their behavior can be subjective, it can be hard to measure responses in an experiment. In addition, political pressure may alter the results. The subjects may not be a good representation of the population, or groups used may not be comparable.

And finally, since researchers are human too, results may be degraded due to human error.

What This Means For You

Every psychological research method has its pros and cons. The experimental method can help establish cause and effect, and it's also beneficial when research funds are limited or time is of the essence.

At the same time, it's essential to be aware of this method's pitfalls, such as how biases can affect the results or the potential for low reliability. Keeping these in mind can help you review and assess research studies more accurately, giving you a better idea of whether the results can be trusted or have limitations.

Colorado State University. Experimental and quasi-experimental research .

American Psychological Association. Experimental psychology studies human and animals .

Mayrhofer R, Kuhbandner C, Lindner C. The practice of experimental psychology: An inevitably postmodern endeavor . Front Psychol . 2021;11:612805. doi:10.3389/fpsyg.2020.612805

Mandler G. A History of Modern Experimental Psychology .

Stanford University. Wilhelm Maximilian Wundt . Stanford Encyclopedia of Philosophy.

Britannica. Gustav Fechner .

Britannica. Hermann von Helmholtz .

Meyer A, Hackert B, Weger U. Franz Brentano and the beginning of experimental psychology: implications for the study of psychological phenomena today . Psychol Res . 2018;82:245-254. doi:10.1007/s00426-016-0825-7

Britannica. Georg Elias Müller .

McCambridge J, de Bruin M, Witton J.  The effects of demand characteristics on research participant behaviours in non-laboratory settings: A systematic review .  PLoS ONE . 2012;7(6):e39116. doi:10.1371/journal.pone.0039116

Laboratory experiments . In: The Sage Encyclopedia of Communication Research Methods. Allen M, ed. SAGE Publications, Inc. doi:10.4135/9781483381411.n287

Schweizer M, Braun B, Milstone A. Research methods in healthcare epidemiology and antimicrobial stewardship — quasi-experimental designs . Infect Control Hosp Epidemiol . 2016;37(10):1135-1140. doi:10.1017/ice.2016.117

Glass A, Kang M. Dividing attention in the classroom reduces exam performance . Educ Psychol . 2019;39(3):395-408. doi:10.1080/01443410.2018.1489046

Keskin M, Ooms K, Dogru AO, De Maeyer P. Exploring the cognitive load of expert and novice map users using EEG and eye tracking . ISPRS Int J Geo-Inf . 2020;9(7):429. doi:10.3390.ijgi9070429

Ho A, Hancock J, Miner A. Psychological, relational, and emotional effects of self-disclosure after conversations with a chatbot . J Commun . 2018;68(4):712-733. doi:10.1093/joc/jqy026

Haynes IV J, Frith E, Sng E, Loprinzi P. Experimental effects of acute exercise on episodic memory function: Considerations for the timing of exercise . Psychol Rep . 2018;122(5):1744-1754. doi:10.1177/0033294118786688

Torresin S, Pernigotto G, Cappelletti F, Gasparella A. Combined effects of environmental factors on human perception and objective performance: A review of experimental laboratory works . Indoor Air . 2018;28(4):525-538. doi:10.1111/ina.12457

Schumpe BM, Belanger JJ, Moyano M, Nisa CF. The role of sensation seeking in political violence: An extension of the significance quest theory . J Personal Social Psychol . 2020;118(4):743-761. doi:10.1037/pspp0000223

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

Princeton Correspondents on Undergraduate Research

How to Write An Effective Lab Report

Whether you are in lab for general chemistry, independent work, or senior thesis, almost all lab experiments will be followed up with a lab report or paper. Although it should be relatively easy to write about an experiment you completed, this is often the most difficult part of lab work, especially when the results are unexpected. In this post, I will outline the components of a lab report while offering tips on how to write one.

Understand Your Experiments Thoroughly

Before you begin writing your draft, it is important that you understand your experiment, as this will help you decide what to include in your paper. When I wrote my first organic chemistry lab report, I rushed to begin answering the discussion questions only to realize halfway through that I had a major conceptual error. Because of this, I had to revise most of what I had written so far, which cost me a lot of time. Know what the purpose of the lab is, formulate the hypothesis, and begin to think about the results you are expecting. At this point, it is helpful to check in with your Lab TA, mentor, or principal investigator (PI) to ensure that you thoroughly understand your project. 

The abstract of your lab report will generally consist of a short summary of your entire report, typically in the same order as your report. Although this is the first section of your lab report, this should be the last section you write. Rather than trying to follow your entire report based on your abstract, it is easier if you write your report first before trying to summarize it.

Introduction and Background

The introduction and background of your report should establish the purpose of your experiment (what principles you are examining), your hypothesis (what you expect to see and why), and relevant findings from others in the field. You have likely done extensive reading about the project from textbooks, lecture notes, or scholarly articles. But as you write, only include background information that is relevant to your specific experiments. For instance, over the summer when I was still learning about metabolic engineering and its role in yeast cells, I read several articles detailing this process. However, a lot of this information was a very broad introduction to the field and not directly related to my project, so I decided not to include most of it. 

This section of the lab report should not contain a step-by-step procedure of your experiments, but rather enough details should be included so that someone else can understand and replicate what you did. From this section, the reader should understand how you tested your hypothesis and why you chose that method. Explain the different parts of your project, the variables being tested, and controls in your experiments. This section will validate the data presented by confirming that variables are being tested in a proper way.

You cannot change the data you collect from your experiments; thus the results section will be written for you. Your job is to present these results in appropriate tables and charts. Depending on the length of your project, you may have months of data from experiments or just a three-hour lab period worth of results. For example, for in-class lab reports, there is usually only one major experiment, so I include most of the data I collect in my lab report. But for longer projects such as summer internships, there are various preliminary experiments throughout, so I select the data to include. Although you cannot change the data, you must choose what is relevant to include in your report. Determine what is included in your report based on the goals and purpose of your project.

Discussion and Conclusion

In this section, you should analyze your results and relate your data back to your hypothesis. You should mention whether the results you obtained matched what was expected and the conclusions that can be drawn from this. For this section, you should talk about your data and conclusions with your lab mentors or TAs before you begin writing. As I mentioned above, by consulting with your mentors, you will avoid making large conceptual error that may take a long time to address.

There is no correct order for how to write a report, but it is generally easier to write some sections before others. For instance, because your results cannot be changed, it is easier to write the results section first. Likewise, because you also cannot change the methods you used in your experiment, it is helpful to write this section after writing your results. Although there are multiple ways to write and format a lab report or research paper, the goals of every report are the same: to describe what you did, your results, and why they are significant. As you write, keep your audience and these goals in mind.

— Saira Reyes, Engineering Correspondent

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Writing a lab report: introduction and discussion section guide.

In an effort to make our handouts more accessible, we have begun converting our PDF handouts to web pages. Download this page as a PDF:   Writing a Lab Report Return to Writing Studio Handouts

Part 1 (of 2): Introducing a Lab Report

The introduction of a lab report states the objective of the experiment and provides the reader with background information. State the topic of your report clearly and concisely (in one or two sentences). Provide background theory, previous research, or formulas the reader should know. Usually, an instructor does not want you to repeat whatever the lab manual says, but to show your understanding of the problem.

Questions an Effective Lab Report Introduction Should Answer

What is the problem.

Describe the problem investigated. Summarize relevant research to provide context, key terms, and concepts so that your reader can understand the experiment.

Why is it important?

Review relevant research to provide a rationale for the investigation. What conflict, unanswered question, untested population, or untried method in existing research does your experiment address? How will you challenge or extend the findings of other researchers?

What solution (or step toward a solution) do you propose?

Briefly describe your experiment : hypothesis , research question , general experimental design or method , and a justification of your method (if alternatives exist).

Tips on Composing Your Lab Report’s Introduction

• Move from the general to the specific – from a problem in research literature to the specifics of your experiment.
• Engage your reader – answer the questions: “What did I do?” “Why should my reader care?”
• Clarify the links between problem and solution, between question asked and research design, and between prior research and the specifics of your experiment.
• Be selective, not exhaustive, in choosing studies to cite and the amount of detail to include. In general, the more relevant an article is to your study, the more space it deserves and the later in the introduction it appears.
• Ask your instructor whether or not you should summarize results and/or conclusions in the Introduction.
• “The objective of the experiment was …”
• “The purpose of this report is …”
• “Bragg’s Law for diffraction is …”
• “The scanning electron microscope produces micrographs …”

Part 2 (of 2): Writing the “Discussion” Section of a Lab Report

The discussion is the most important part of your lab report, because here you show that you have not merely completed the experiment, but that you also understand its wider implications. The discussion section is reserved for putting experimental results in the context of the larger theory. Ask yourself: “What is the significance or meaning of the results?”

Elements of an Effective Discussion Section

What do the results indicate clearly? Based on your results, explain what you know with certainty and draw conclusions.

Interpretation

What is the significance of your results? What ambiguities exist? What are logical explanations for problems in the data? What questions might you raise about the methods used or the validity of the experiment? What can be logically deduced from your analysis?

Tips on the Discussion Section

1. explain your results in terms of theoretical issues..

How well has the theory been illustrated? What are the theoretical implications and practical applications of your results?

For each major result:

• Describe the patterns, principles, and relationships that your results show.
• Explain how your results relate to expectations and to literature cited in your Introduction. Explain any agreements, contradictions, or exceptions.
• Describe what additional research might resolve contradictions or explain exceptions.

2. Relate results to your experimental objective(s).

If you set out to identify an unknown metal by finding its lattice parameter and its atomic structure, be sure that you have identified the metal and its attributes.

3. Compare expected results with those obtained.

If there were differences, how can you account for them? Were the instruments able to measure precisely? Was the sample contaminated? Did calculated values take account of friction?

4. Analyze experimental error along with the strengths and limitations of the experiment’s design.

Were any errors avoidable? Were they the result of equipment?  If the flaws resulted from the experiment design, explain how the design might be improved. Consider, as well, the precision of the instruments that were used.

5. Compare your results to similar investigations.

In some cases, it is legitimate to compare outcomes with classmates, not in order to change your answer, but in order to look for and to account for or analyze any anomalies between the groups. Also, consider comparing your results to published scientific literature on the topic.

The “Introducing a Lab Report” guide was adapted from the University of Toronto Engineering Communications Centre and University of Wisconsin-Madison Writing Center.

The “Writing the Discussion Section of a Lab Report” resource was adapted from the University of Toronto Engineering Communications Centre and University of Wisconsin-Madison Writing Center.

Last revised: 07/2008 | Adapted for web delivery: 02/2021

In order to access certain content on this page, you may need to download Adobe Acrobat Reader or an equivalent PDF viewer software.

What Is a Hypothesis? (Science)

If...,Then...

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A hypothesis (plural hypotheses) is a proposed explanation for an observation. The definition depends on the subject.

In science, a hypothesis is part of the scientific method. It is a prediction or explanation that is tested by an experiment. Observations and experiments may disprove a scientific hypothesis, but can never entirely prove one.

In the study of logic, a hypothesis is an if-then proposition, typically written in the form, "If X , then Y ."

In common usage, a hypothesis is simply a proposed explanation or prediction, which may or may not be tested.

Writing a Hypothesis

Most scientific hypotheses are proposed in the if-then format because it's easy to design an experiment to see whether or not a cause and effect relationship exists between the independent variable and the dependent variable . The hypothesis is written as a prediction of the outcome of the experiment.

Null Hypothesis and Alternative Hypothesis

Statistically, it's easier to show there is no relationship between two variables than to support their connection. So, scientists often propose the null hypothesis . The null hypothesis assumes changing the independent variable will have no effect on the dependent variable.

In contrast, the alternative hypothesis suggests changing the independent variable will have an effect on the dependent variable. Designing an experiment to test this hypothesis can be trickier because there are many ways to state an alternative hypothesis.

For example, consider a possible relationship between getting a good night's sleep and getting good grades. The null hypothesis might be stated: "The number of hours of sleep students get is unrelated to their grades" or "There is no correlation between hours of sleep and grades."

An experiment to test this hypothesis might involve collecting data, recording average hours of sleep for each student and grades. If a student who gets eight hours of sleep generally does better than students who get four hours of sleep or 10 hours of sleep, the hypothesis might be rejected.

But the alternative hypothesis is harder to propose and test. The most general statement would be: "The amount of sleep students get affects their grades." The hypothesis might also be stated as "If you get more sleep, your grades will improve" or "Students who get nine hours of sleep have better grades than those who get more or less sleep."

In an experiment, you can collect the same data, but the statistical analysis is less likely to give you a high confidence limit.

Usually, a scientist starts out with the null hypothesis. From there, it may be possible to propose and test an alternative hypothesis, to narrow down the relationship between the variables.

Example of a Hypothesis

Examples of a hypothesis include:

• If you drop a rock and a feather, (then) they will fall at the same rate.
• Plants need sunlight in order to live. (if sunlight, then life)
• Eating sugar gives you energy. (if sugar, then energy)
• White, Jay D.  Research in Public Administration . Conn., 1998.
• Schick, Theodore, and Lewis Vaughn.  How to Think about Weird Things: Critical Thinking for a New Age . McGraw-Hill Higher Education, 2002.
• Scientific Method Flow Chart
• Six Steps of the Scientific Method
• What Are the Elements of a Good Hypothesis?
• What Are Examples of a Hypothesis?
• What Is a Testable Hypothesis?
• Null Hypothesis Examples
• Scientific Hypothesis Examples
• Scientific Variable
• Scientific Method Vocabulary Terms
• Understanding Simple vs Controlled Experiments
• What Is a Controlled Experiment?
• What Is an Experimental Constant?
• What Is the Difference Between a Control Variable and Control Group?
• DRY MIX Experiment Variables Acronym
• Random Error vs. Systematic Error
• The Role of a Controlled Variable in an Experiment

How to Develop a Good Research Hypothesis

The story of a research study begins by asking a question. Researchers all around the globe are asking curious questions and formulating research hypothesis. However, whether the research study provides an effective conclusion depends on how well one develops a good research hypothesis. Research hypothesis examples could help researchers get an idea as to how to write a good research hypothesis.

This blog will help you understand what is a research hypothesis, its characteristics and, how to formulate a research hypothesis

Table of Contents

What is Hypothesis?

Hypothesis is an assumption or an idea proposed for the sake of argument so that it can be tested. It is a precise, testable statement of what the researchers predict will be outcome of the study.  Hypothesis usually involves proposing a relationship between two variables: the independent variable (what the researchers change) and the dependent variable (what the research measures).

What is a Research Hypothesis?

Research hypothesis is a statement that introduces a research question and proposes an expected result. It is an integral part of the scientific method that forms the basis of scientific experiments. Therefore, you need to be careful and thorough when building your research hypothesis. A minor flaw in the construction of your hypothesis could have an adverse effect on your experiment. In research, there is a convention that the hypothesis is written in two forms, the null hypothesis, and the alternative hypothesis (called the experimental hypothesis when the method of investigation is an experiment).

Characteristics of a Good Research Hypothesis

As the hypothesis is specific, there is a testable prediction about what you expect to happen in a study. You may consider drawing hypothesis from previously published research based on the theory.

A good research hypothesis involves more effort than just a guess. In particular, your hypothesis may begin with a question that could be further explored through background research.

To help you formulate a promising research hypothesis, you should ask yourself the following questions:

• Is the language clear and focused?
• What is the relationship between your hypothesis and your research topic?
• Is your hypothesis testable? If yes, then how?
• What are the possible explanations that you might want to explore?
• Does your hypothesis include both an independent and dependent variable?
• Can you manipulate your variables without hampering the ethical standards?
• Does your research predict the relationship and outcome?
• Is your research simple and concise (avoids wordiness)?
• Is it clear with no ambiguity or assumptions about the readers’ knowledge
• Is your research observable and testable results?
• Is it relevant and specific to the research question or problem?

The questions listed above can be used as a checklist to make sure your hypothesis is based on a solid foundation. Furthermore, it can help you identify weaknesses in your hypothesis and revise it if necessary.

Source: Educational Hub

How to formulate a research hypothesis.

A testable hypothesis is not a simple statement. It is rather an intricate statement that needs to offer a clear introduction to a scientific experiment, its intentions, and the possible outcomes. However, there are some important things to consider when building a compelling hypothesis.

1. State the problem that you are trying to solve.

Make sure that the hypothesis clearly defines the topic and the focus of the experiment.

2. Try to write the hypothesis as an if-then statement.

Follow this template: If a specific action is taken, then a certain outcome is expected.

3. Define the variables

Independent variables are the ones that are manipulated, controlled, or changed. Independent variables are isolated from other factors of the study.

Dependent variables , as the name suggests are dependent on other factors of the study. They are influenced by the change in independent variable.

4. Scrutinize the hypothesis

Evaluate assumptions, predictions, and evidence rigorously to refine your understanding.

Types of Research Hypothesis

The types of research hypothesis are stated below:

1. Simple Hypothesis

It predicts the relationship between a single dependent variable and a single independent variable.

2. Complex Hypothesis

It predicts the relationship between two or more independent and dependent variables.

3. Directional Hypothesis

It specifies the expected direction to be followed to determine the relationship between variables and is derived from theory. Furthermore, it implies the researcher’s intellectual commitment to a particular outcome.

4. Non-directional Hypothesis

It does not predict the exact direction or nature of the relationship between the two variables. The non-directional hypothesis is used when there is no theory involved or when findings contradict previous research.

5. Associative and Causal Hypothesis

The associative hypothesis defines interdependency between variables. A change in one variable results in the change of the other variable. On the other hand, the causal hypothesis proposes an effect on the dependent due to manipulation of the independent variable.

6. Null Hypothesis

Null hypothesis states a negative statement to support the researcher’s findings that there is no relationship between two variables. There will be no changes in the dependent variable due the manipulation of the independent variable. Furthermore, it states results are due to chance and are not significant in terms of supporting the idea being investigated.

7. Alternative Hypothesis

It states that there is a relationship between the two variables of the study and that the results are significant to the research topic. An experimental hypothesis predicts what changes will take place in the dependent variable when the independent variable is manipulated. Also, it states that the results are not due to chance and that they are significant in terms of supporting the theory being investigated.

Research Hypothesis Examples of Independent and Dependent Variables

Research Hypothesis Example 1 The greater number of coal plants in a region (independent variable) increases water pollution (dependent variable). If you change the independent variable (building more coal factories), it will change the dependent variable (amount of water pollution).

Research Hypothesis Example 2 What is the effect of diet or regular soda (independent variable) on blood sugar levels (dependent variable)? If you change the independent variable (the type of soda you consume), it will change the dependent variable (blood sugar levels)

You should not ignore the importance of the above steps. The validity of your experiment and its results rely on a robust testable hypothesis. Developing a strong testable hypothesis has few advantages, it compels us to think intensely and specifically about the outcomes of a study. Consequently, it enables us to understand the implication of the question and the different variables involved in the study. Furthermore, it helps us to make precise predictions based on prior research. Hence, forming a hypothesis would be of great value to the research. Here are some good examples of testable hypotheses.

More importantly, you need to build a robust testable research hypothesis for your scientific experiments. A testable hypothesis is a hypothesis that can be proved or disproved as a result of experimentation.

Importance of a Testable Hypothesis

To devise and perform an experiment using scientific method, you need to make sure that your hypothesis is testable. To be considered testable, some essential criteria must be met:

• There must be a possibility to prove that the hypothesis is true.
• There must be a possibility to prove that the hypothesis is false.
• The results of the hypothesis must be reproducible.

Without these criteria, the hypothesis and the results will be vague. As a result, the experiment will not prove or disprove anything significant.

What are your experiences with building hypotheses for scientific experiments? What challenges did you face? How did you overcome these challenges? Please share your thoughts with us in the comments section.

Frequently Asked Questions

The steps to write a research hypothesis are: 1. Stating the problem: Ensure that the hypothesis defines the research problem 2. Writing a hypothesis as an 'if-then' statement: Include the action and the expected outcome of your study by following a ‘if-then’ structure. 3. Defining the variables: Define the variables as Dependent or Independent based on their dependency to other factors. 4. Scrutinizing the hypothesis: Identify the type of your hypothesis

Hypothesis testing is a statistical tool which is used to make inferences about a population data to draw conclusions for a particular hypothesis.

Hypothesis in statistics is a formal statement about the nature of a population within a structured framework of a statistical model. It is used to test an existing hypothesis by studying a population.

Research hypothesis is a statement that introduces a research question and proposes an expected result. It forms the basis of scientific experiments.

The different types of hypothesis in research are: • Null hypothesis: Null hypothesis is a negative statement to support the researcher’s findings that there is no relationship between two variables. • Alternate hypothesis: Alternate hypothesis predicts the relationship between the two variables of the study. • Directional hypothesis: Directional hypothesis specifies the expected direction to be followed to determine the relationship between variables. • Non-directional hypothesis: Non-directional hypothesis does not predict the exact direction or nature of the relationship between the two variables. • Simple hypothesis: Simple hypothesis predicts the relationship between a single dependent variable and a single independent variable. • Complex hypothesis: Complex hypothesis predicts the relationship between two or more independent and dependent variables. • Associative and casual hypothesis: Associative and casual hypothesis predicts the relationship between two or more independent and dependent variables. • Empirical hypothesis: Empirical hypothesis can be tested via experiments and observation. • Statistical hypothesis: A statistical hypothesis utilizes statistical models to draw conclusions about broader populations.

Wow! You really simplified your explanation that even dummies would find it easy to comprehend. Thank you so much.

Thanks a lot for your valuable guidance.

I enjoy reading the post. Hypotheses are actually an intrinsic part in a study. It bridges the research question and the methodology of the study.

Useful piece!

This is awesome.Wow.

It very interesting to read the topic, can you guide me any specific example of hypothesis process establish throw the Demand and supply of the specific product in market

Nicely explained

It is really a useful for me Kindly give some examples of hypothesis

It was a well explained content ,can you please give me an example with the null and alternative hypothesis illustrated

clear and concise. thanks.

So Good so Amazing

Good to learn

Thanks a lot for explaining to my level of understanding

Explained well and in simple terms. Quick read! Thank you

It awesome. It has really positioned me in my research project

Brief and easily digested

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Experiment Definition in Science – What Is a Science Experiment?

In science, an experiment is simply a test of a hypothesis in the scientific method . It is a controlled examination of cause and effect. Here is a look at what a science experiment is (and is not), the key factors in an experiment, examples, and types of experiments.

Experiment Definition in Science

By definition, an experiment is a procedure that tests a hypothesis. A hypothesis, in turn, is a prediction of cause and effect or the predicted outcome of changing one factor of a situation. Both the hypothesis and experiment are components of the scientific method. The steps of the scientific method are:

• Make observations.
• Ask a question or identify a problem.
• State a hypothesis.
• Perform an experiment that tests the hypothesis.
• Based on the results of the experiment, either accept or reject the hypothesis.
• Draw conclusions and report the outcome of the experiment.

Key Parts of an Experiment

The two key parts of an experiment are the independent and dependent variables. The independent variable is the one factor that you control or change in an experiment. The dependent variable is the factor that you measure that responds to the independent variable. An experiment often includes other types of variables , but at its heart, it’s all about the relationship between the independent and dependent variable.

Examples of Experiments

Fertilizer and plant size.

For example, you think a certain fertilizer helps plants grow better. You’ve watched your plants grow and they seem to do better when they have the fertilizer compared to when they don’t. But, observations are only the beginning of science. So, you state a hypothesis: Adding fertilizer increases plant size. Note, you could have stated the hypothesis in different ways. Maybe you think the fertilizer increases plant mass or fruit production, for example. However you state the hypothesis, it includes both the independent and dependent variables. In this case, the independent variable is the presence or absence of fertilizer. The dependent variable is the response to the independent variable, which is the size of the plants.

Now that you have a hypothesis, the next step is designing an experiment that tests it. Experimental design is very important because the way you conduct an experiment influences its outcome. For example, if you use too small of an amount of fertilizer you may see no effect from the treatment. Or, if you dump an entire container of fertilizer on a plant you could kill it! So, recording the steps of the experiment help you judge the outcome of the experiment and aid others who come after you and examine your work. Other factors that might influence your results might include the species of plant and duration of the treatment. Record any conditions that might affect the outcome. Ideally, you want the only difference between your two groups of plants to be whether or not they receive fertilizer. Then, measure the height of the plants and see if there is a difference between the two groups.

Salt and Cookies

You don’t need a lab for an experiment. For example, consider a baking experiment. Let’s say you like the flavor of salt in your cookies, but you’re pretty sure the batch you made using extra salt fell a bit flat. If you double the amount of salt in a recipe, will it affect their size? Here, the independent variable is the amount of salt in the recipe and the dependent variable is cookie size.

Test this hypothesis with an experiment. Bake cookies using the normal recipe (your control group ) and bake some using twice the salt (the experimental group). Make sure it’s the exact same recipe. Bake the cookies at the same temperature and for the same time. Only change the amount of salt in the recipe. Then measure the height or diameter of the cookies and decide whether to accept or reject the hypothesis.

Examples of Things That Are Not Experiments

Based on the examples of experiments, you should see what is not an experiment:

• Making observations does not constitute an experiment. Initial observations often lead to an experiment, but are not a substitute for one.
• Making a model is not an experiment.
• Neither is making a poster.
• Just trying something to see what happens is not an experiment. You need a hypothesis or prediction about the outcome.
• Changing a lot of things at once isn’t an experiment. You only have one independent and one dependent variable. However, in an experiment, you might suspect the independent variable has an effect on a separate. So, you design a new experiment to test this.

Types of Experiments

There are three main types of experiments: controlled experiments, natural experiments, and field experiments,

• Controlled experiment : A controlled experiment compares two groups of samples that differ only in independent variable. For example, a drug trial compares the effect of a group taking a placebo (control group) against those getting the drug (the treatment group). Experiments in a lab or home generally are controlled experiments
• Natural experiment : Another name for a natural experiment is a quasi-experiment. In this type of experiment, the researcher does not directly control the independent variable, plus there may be other variables at play. Here, the goal is establishing a correlation between the independent and dependent variable. For example, in the formation of new elements a scientist hypothesizes that a certain collision between particles creates a new atom. But, other outcomes may be possible. Or, perhaps only decay products are observed that indicate the element, and not the new atom itself. Many fields of science rely on natural experiments, since controlled experiments aren’t always possible.
• Field experiment : While a controlled experiments takes place in a lab or other controlled setting, a field experiment occurs in a natural setting. Some phenomena cannot be readily studied in a lab or else the setting exerts an influence that affects the results. So, a field experiment may have higher validity. However, since the setting is not controlled, it is also subject to external factors and potential contamination. For example, if you study whether a certain plumage color affects bird mate selection, a field experiment in a natural environment eliminates the stressors of an artificial environment. Yet, other factors that could be controlled in a lab may influence results. For example, nutrition and health are controlled in a lab, but not in the field.
• Bailey, R.A. (2008). Design of Comparative Experiments . Cambridge: Cambridge University Press. ISBN 9780521683579.
• di Francia, G. Toraldo (1981). The Investigation of the Physical World . Cambridge University Press. ISBN 0-521-29925-X.
• Hinkelmann, Klaus; Kempthorne, Oscar (2008). Design and Analysis of Experiments. Volume I: Introduction to Experimental Design (2nd ed.). Wiley. ISBN 978-0-471-72756-9.
• Holland, Paul W. (December 1986). “Statistics and Causal Inference”.  Journal of the American Statistical Association . 81 (396): 945–960. doi: 10.2307/2289064
• Stohr-Hunt, Patricia (1996). “An Analysis of Frequency of Hands-on Experience and Science Achievement”. Journal of Research in Science Teaching . 33 (1): 101–109. doi: 10.1002/(SICI)1098-2736(199601)33:1<101::AID-TEA6>3.0.CO;2-Z

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

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

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

There are 5 main steps in hypothesis testing:

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

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

Table of contents

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Methodology

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

Research bias

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

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

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

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

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

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Loftus and Palmer (1974): Car Crash Experiment

Saul McLeod, PhD

Editor-in-Chief for Simply Psychology

BSc (Hons) Psychology, MRes, PhD, University of Manchester

Saul McLeod, PhD., is a qualified psychology teacher with over 18 years of experience in further and higher education. He has been published in peer-reviewed journals, including the Journal of Clinical Psychology.

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Psychologist Elizabeth Loftus has been particularly concerned with how subsequent information can affect an eyewitness’s account of an event.

Her main focus has been on the influence of (mis)leading information regarding both visual imagery and wording of questions concerning eyewitness testimony.

A  leading question  is a question that suggests what answer is desired or leads to the desired answer.

Loftus’ findings indicate that memory for an event that has been witnessed is highly flexible.  If someone is exposed to new information during the interval between witnessing the event and recalling it, this new information may have marked effects on what they recall.  The original memory can be modified, changed or supplemented.

The fact that eyewitness testimony can be unreliable and influenced by leading questions is illustrated by the classic psychology study by Loftus and Palmer (1974), Reconstruction of Automobile Destruction, described below.

To test their hypothesis that the language used in eyewitness testimony can alter memory.

Thus, they aimed to show that leading questions could distort eyewitness testimony accounts and so have a confabulating effect, as the account would become distorted by cues provided in the question.

To test this, Loftus and Palmer (1974) asked people to estimate the speed of motor vehicles using different forms of questions.

Estimating vehicle speed is something people are generally poor at, so they may be more open to suggestions.

Experiment One:  5 verbs in leading questions

Forty-five American students from the University of Washington formed an opportunity sample.

This was a laboratory experiment with five conditions, only one of which was experienced by each participant (an independent measures experimental design ).

Seven films of traffic accidents, ranging in duration from 5 to 30 seconds, were presented to each group in random order.

After watching the film, participants were asked to describe what had happened as if they were eyewitnesses.

They were then asked specific questions, including the question “About how fast were the cars going when they (smashed / collided / bumped / hit / contacted) each other?”

Thus, the IV was the verb of the question, and the DV was the speed reported by the participants.

The estimated speed was affected by the verb used. The verb implied information about the speed, which systematically affected the participants’ memory of the accident.

Participants who were asked the “smashed” question thought the cars were going faster than those who were asked the “hit” question.

The participants in the “smashed” condition reported the highest speed estimate (40.8 mph), followed by “collided” (39.3 mph), “bumped” (38.1 mph), “hit” (34 mph), and “contacted” (31.8 mph) in descending order.

The results show that the verb conveyed an impression of the speed the car was traveling and this altered the participants” perceptions.

In other words, eyewitness testimony might be biased by the way questions are asked after a crime is committed.

Loftus and Palmer offer two possible explanations for this result:

• Response-bias factors : The misleading information provided may have influenced the answer a person gave (a “response-bias”), but didn’t actually lead to a false memory of the event. For example, the different speed estimates occur because the critical word (e.g., “smash” or “hit”) influences or biases a person’s response.
• The memory representation is altered : The critical verb changes a person’s perception of the accident—some critical words would lead someone to perceive the accident as more serious. This perception is then stored in a person’s memory of the event.

If the second explanation is true, we expect participants to remember other details that are not. Loftus and Palmer tested this in their second experiment.

Experiment Two: The broken glass manipulation

A second experiment was conducted with the aim of investigating is leading questions simply create a response bias, or if they actually alter a person’s memory representation.

150 students were shown a one-minute film which featured a car driving through the countryside followed by four seconds of a multiple traffic accident.

Afterward, the students were questioned about the film. The independent variable was the type of question asked.

• 50 participants were asked “how fast were the car going when they hit each other?”,
• 50 participants were asked, “How fast were the cars going when they smashed each other?”
• the remaining 50 participants were not asked a question about the car’s speed (i.e., the control group).

One week later, the dependent variable was measured – without seeing the film again, they answered ten questions, one of which was a critical one randomly placed in the list:

“Did you see any broken glass? Yes or no?”

There was no broken glass in the original film.

Participants were asked how fast the cars were going when they smashed were more likely to report seeing broken glass.

This research suggests that questioning techniques easily distorts memory, and information acquired after an event can merge with original memory, causing inaccurate recall or reconstructive memory.

The results from experiment two suggest that this effect is not just due to a response bias because leading questions altered the participant’s memory for the event.

The addition of false details to a memory of an event is referred to as confabulation. This has important implications for the questions used in police interviews of eyewitnesses .

Consequently, Loftus and Palmer support the reconstructive memory hypothesis – arguing that information gathered at the time of an event is modified by data gathered afterward.

Over time, information from these two sources is integrated so that it is impossible to separate them—in effect, we have only one memory.

High level of control

Perhaps the greatest strength of Loftus and Palmer’s experiment is the degree of control over confounding variables . As the study was lab-based, the researchers could ensure that a range of factors (age of participants, incident viewed, environment, etc).

Consequently, they could ensure that these factors did not affect the respondents’ answers and that only the verb condition was causing the participants to reevaluate their memories.

Practical Implications

The reconstructive memory hypothesis is extremely useful as a psychological explanation, for instance, in formulating guidelines for police questioning witnesses and suspects.

The conclusion that leading questions can affect memory has important implications for interviewing witnesses , both by police immediately or soon after an event and also by lawyers in court sometime later.

Interviewers should avoid leading questions and be careful to word questions in a way that does not suggest an answer to the person they are interviewing.

The study also had real-world implications; based on evidence such as Loftus’s, the Devlin Report (1976) recommended that trial judges instruct juries that it is not safe to convict on a single eyewitness testimony alone.

A strength of the study is it’s easy to replicate (i.e. copy). This is because the method was a laboratory experiment which followed a standardized procedure.

Low ecological validity

One limitation of the research is that it lacked mundane realism / ecological validity. Participants viewed video clips rather than being present at a real-life accident.

As the video clip does not have the same emotional impact as witnessing a real-life accident, the participants would be less likely to pay attention and less motivated to be accurate in their judgments.

Furthermore, watching a real crash provides much more context—the participants were cued to watch the video, whereas crashes in real life are largely unexpected.

In an experiment, you may expect to be asked questions about what you are watching, which may make you attend the film differently.

In real life, the answers you give may have consequences, which may put pressure on the witness.

Overall, we can probably conclude that this laboratory experiment had low ecological validity and thus may not tell us very much about how people’s memories are affected by leading questions in real life.

Conflicting research

A study conducted by Yuille and Cutshall (1986) conflicts with the findings of this study. They found that misleading information did not alter the memory of people who had witnessed a real armed robbery.

This implies that misleading information may have a greater influence in the lab rather and that Loftus and Palmer’s study may have lacked ecological validity.

He was especially interested in the characteristics of people whom he considered to have achieved their potential as individuals.

Biased Sample

A further problem with the study was the use of students as participants. Students are not representative of the general population in several ways.

Differences between students and the broader population, such as age, memory abilities, learning habits, driving experience, and susceptibility to demand characteristics, could make it difficult to generalize the findings.

Importantly, they may be less experienced drivers and, therefore, less confident in their ability to estimate speeds. This may have influenced them to be more swayed by the verb in the question.

Demand Characteristics

Participants know they are in a laboratory experiment, which will affect their behavior in several ways. They will be looking for clues on how to behave (demand characteristics), and they will usually want to help the experimenters by giving them the results they think they want.

We cannot know that the leading questions had irretrievably altered the participants’ original memories.

Instead, participants could merely be following the researcher’s suggestions in both the original round of questions and the follow-up questions.

In effect, demand characteristics could be “carried forward” – as participants remembered being asked about the cars “smashing” into each other, they were prompted to say that they had seen broken glass in the follow-up study.

Independent Learning Tasks

• Draw a table showing the results of experiment one and draw a bar chart to show the results of experiment two.
• Read the original article of the study.
• Conduct your own study repeating one of the experiments by Loftus and Palmer.
• Use photographs (or video clips) of car accidents and write a set of questions, one of which will be the critical question.
• Test one group of participants using the “smashed” condition and the other group with the “hit” condition.
• Calculate the mean, median and mode speed estimates for both the “smashed” and “hit” conditions. Illustrate your results in either a table or graph.

Learning Check (1)

• Write an experimental hypothesis for experiment 1. Make sure it is clearly operationalized and include the independent and dependent variables.
• Why was it a good idea to ask 10 questions rather than just asking the critical question alone?
• Why was each group of participants shown the 7 video clips (of car accidents) in a different order?
• Outline the possible sampling technique that may have been used in this study.
• The participants knew they were taking part in a psychology experiment. How do you think this may have effected their behavior?
• Can you think of a way that this problem might of been overcome?

Learning Check (2)

• Write a null hypothesis for experiment 2. Make sure it is clearly operationalized and include the independent and dependent variables.
• What is a “control group”, and why is it necessary?
• What is an “experimental” group?
• Outline one difference between the responses given between the two experimental groups.
• Outline the quantitative measure used in this study.

Devlin Committee Report: Report of the Committee on Evidence of Identification in Criminal Cases, 1976 Cmnd 338 134/135, 42

Loftus, E. F., & Palmer, J. C. (1974). Reconstruction of auto-mobile destruction : An example of the interaction between language and memory. Journal of Verbal Learning and Verbal behavior , 13, 585-589.

Yuille, J. C., & Cutshall, J. L. (1986). A case study of eyewitness memory of a crime. Journal of Applied Psychology, 71(2), 291.