research null hypothesis maker

Hypothesis Maker Online

Looking for a hypothesis maker? This online tool for students will help you formulate a beautiful hypothesis quickly, efficiently, and for free.

Are you looking for an effective hypothesis maker online? Worry no more; try our online tool for students and formulate your hypothesis within no time.

• 🔎 How to Use the Tool?
• ⚗️ What Is a Hypothesis in Science?

👍 What Does a Good Hypothesis Mean?

• 🧭 Steps to Making a Good Hypothesis

🔗 References

📄 hypothesis maker: how to use it.

Our hypothesis maker is a simple and efficient tool you can access online for free.

If you want to create a research hypothesis quickly, you should fill out the research details in the given fields on the hypothesis generator.

Below are the fields you should complete to generate your hypothesis:

• Who or what is your research based on? For instance, the subject can be research group 1.
• What does the subject (research group 1) do?
• What does the subject affect? - This shows the predicted outcome, which is the object.
• Who or what will be compared with research group 1? (research group 2).

Once you fill the in the fields, you can click the ‘Make a hypothesis’ tab and get your results.

⚗️ What Is a Hypothesis in the Scientific Method?

A hypothesis is a statement describing an expectation or prediction of your research through observation.

It is similar to academic speculation and reasoning that discloses the outcome of your scientific test . An effective hypothesis, therefore, should be crafted carefully and with precision.

A good hypothesis should have dependent and independent variables . These variables are the elements you will test in your research method – it can be a concept, an event, or an object as long as it is observable.

You can observe the dependent variables while the independent variables keep changing during the experiment.

In a nutshell, a hypothesis directs and organizes the research methods you will use, forming a large section of research paper writing.

Hypothesis vs. Theory

A hypothesis is a realistic expectation that researchers make before any investigation. It is formulated and tested to prove whether the statement is true. A theory, on the other hand, is a factual principle supported by evidence. Thus, a theory is more fact-backed compared to a hypothesis.

Another difference is that a hypothesis is presented as a single statement , while a theory can be an assortment of things . Hypotheses are based on future possibilities toward a specific projection, but the results are uncertain. Theories are verified with undisputable results because of proper substantiation.

When it comes to data, a hypothesis relies on limited information , while a theory is established on an extensive data set tested on various conditions.

You should observe the stated assumption to prove its accuracy.

Since hypotheses have observable variables, their outcome is usually based on a specific occurrence. Conversely, theories are grounded on a general principle involving multiple experiments and research tests.

This general principle can apply to many specific cases.

The primary purpose of formulating a hypothesis is to present a tentative prediction for researchers to explore further through tests and observations. Theories, in their turn, aim to explain plausible occurrences in the form of a scientific study.

It would help to rely on several criteria to establish a good hypothesis. Below are the parameters you should use to analyze the quality of your hypothesis.

🧭 6 Steps to Making a Good Hypothesis

Writing a hypothesis becomes way simpler if you follow a tried-and-tested algorithm. Let’s explore how you can formulate a good hypothesis in a few steps:

Step #1: Ask Questions

The first step in hypothesis creation is asking real questions about the surrounding reality.

Why do things happen as they do? What are the causes of some occurrences?

Your curiosity will trigger great questions that you can use to formulate a stellar hypothesis. So, ensure you pick a research topic of interest to scrutinize the world’s phenomena, processes, and events.

Step #2: Do Initial Research

Carry out preliminary research and gather essential background information about your topic of choice.

The extent of the information you collect will depend on what you want to prove.

Your initial research can be complete with a few academic books or a simple Internet search for quick answers with relevant statistics.

Still, keep in mind that in this phase, it is too early to prove or disapprove of your hypothesis.

Step #3: Identify Your Variables

Now that you have a basic understanding of the topic, choose the dependent and independent variables.

Take note that independent variables are the ones you can’t control, so understand the limitations of your test before settling on a final hypothesis.

Step #4: Formulate Your Hypothesis

You can write your hypothesis as an ‘if – then’ expression . Presenting any hypothesis in this format is reliable since it describes the cause-and-effect you want to test.

For instance: If I study every day, then I will get good grades.

Step #5: Gather Relevant Data

Once you have identified your variables and formulated the hypothesis, you can start the experiment. Remember, the conclusion you make will be a proof or rebuttal of your initial assumption.

So, gather relevant information, whether for a simple or statistical hypothesis, because you need to back your statement.

Step #6: Record Your Findings

Finally, write down your conclusions in a research paper .

Outline in detail whether the test has proved or disproved your hypothesis.

Edit and proofread your work, using a plagiarism checker to ensure the authenticity of your text.

We hope that the above tips will be useful for you. Note that if you need to conduct business analysis, you can use the free templates we’ve prepared: SWOT , PESTLE , VRIO , SOAR , and Porter’s 5 Forces .

❓ Hypothesis Formulator FAQ

Updated: Jul 19th, 2024

• How to Write a Hypothesis in 6 Steps - Grammarly
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IvyPanda's free online hypothesis maker will help you formulate a hypothesis for your study. With this easy-to-use tool, you just need to provide basic info about the focus of your research, its variables, and predicted outcomes. The rest is on us. Get a perfect hypothesis fast!

Research Hypothesis Generator Online

• ️👍 Hypothesis Maker: the Benefits
• ️🔎 How to Use the Tool?
• ️🕵️ What Is a Research Hypothesis?
• ️⚗️ Scientific Method
• ️🔗 References

👍 Hypothesis Maker: the Benefits

Here are the key benefits of this null and alternative hypothesis generator.

🔎 Hypothesis Generator: How to Use It?

Whenever you conduct research, whether a 5-paragraph essay or a more complex assignment, you need to create a hypothesis for this study.

Clueless about how to create a good hypothesis?

No need to waste time and energy on this small portion of your writing process! You can always use our hypothesis creator to get a researchable assumption in no time.

To get a ready-made hypothesis idea, you need to:

• State the object of your study
• Specify what the object does
• Lay out the outcome of that activity
• Indicate the comparison group

Once all data is inserted into the fields, you can press the “Generate now” button and get the result from our hypothesis generator for research paper or any other academic task.

🕵️ What Is a Research Hypothesis?

A hypothesis is your assumption based on existing academic knowledge and observations of the surrounding natural world.

It also involves a healthy portion of intuition because you should arrive at an interesting, commonsense question about the phenomena or processes you observe.

The traditional formula for hypothesis generation is an “if…then” statement, reflecting its falsifiability and testability.

What do these terms mean?

• Testability means you can formulate a scientific guess and test it with data and analysis.
• Falsifiability is a related feature, allowing you to refute the hypothesis with data and show that your guess has no tangible support in real-world data.

For example, you might want to hypothesize the following:

If children are given enough free play time, their intelligence scores rise quicker.

You can test this assumption by observing and measuring two groups – children involved in much free play and those who don’t get free play time. Once the study period ends, you can measure the intelligence scores in both groups to see the difference, thus proving or disproving your hypothesis, which will be testing your hypothesis. If you find tangible differences between the two groups, your hypothesis will be proven, and if there is no difference, the hypothesis will prove false.

Null and Alternative Hypothesis

As a rule, hypotheses are presented in pairs in academic studies, as your scientific guess may be refuted or proved. Thus, you should formulate two hypotheses – a null and alternative variant of the same guess – to see which one is proved with your experiment.

The alternative hypothesis is formulated in an affirmative form, assuming a specific relationship between variables. In other words, you hypothesize that the predetermined outcome will be observed if one condition is met.

Watching films before sleep reduces the quality of sleep.

The null hypothesis is formulated in a negative form, suggesting that there is no association between the variables of your interest. For example:

Watching films before sleep doesn’t affect the quality of sleep.

⚗️ Creating a Hypothesis: the Key Steps

The development and testing of multiple hypotheses are the basis of the scientific method .

Without such inquiries, academic knowledge would never progress, and humanity would remain with a limited understanding of the natural world.

How can you contribute to the existing academic base with well-developed and rigorously planned scientific studies ? Here is an introduction to the empirical method of scientific inquiry.

Step #1: Observe the World Around You

Look around you to see what’s taking place in your academic area. If you’re a biology researcher, look into the untapped biological processes or intriguing facts that nobody has managed to explain before you.

What’s surprising or unusual in your observations? How can you approach this area of interest?

That’s the starting point of an academic journey to new knowledge.

Step #2: Ask Questions

Now that you’ve found a subject of interest, it’s time to generate scientific research questions.

A question can be called scientific if it is well-defined, focuses on measurable dimensions, and is largely testable.

Some hints for a scientific question are:

• What effect does X produce on Y?
• What happens if the intensity of X’s impact reduces or rises?
• What is the primary cause of X?
• How is X related to Y in this group of people?
• How effective is X in the field of C?

As you can see, X is the independent variable , and Y is the dependent variable.

This principle of hypothesis formulation is vital for cases when you want to illustrate or measure the strength of one variable’s effect on the other.

Step #3: Generate a Research Hypothesis

After asking the scientific question, you can hypothesize what your answer to it can be.

You don’t have any data yet to answer the question confidently, but you can assume what effect you will observe during an empirical investigation.

For example, suppose your background research shows that protein consumption boosts muscle growth.

In that case, you can hypothesize that a sample group consuming much protein after physical training will exhibit better muscle growth dynamics compared to those who don’t eat protein. This way, you’re making a scientific guess based on your prior knowledge of the subject and your intuition.

Step #4: Hold an Experiment

With a hypothesis at hand, you can proceed to the empirical study for its testing. As a rule, you should have a clearly formulated methodology for proving or disproving your hypothesis before you create it. Otherwise, how can you know that it is testable? An effective hypothesis usually contains all data about the research context and the population of interest.

For example:

Marijuana consumption among U. S. college students reduces their motivation and academic achievement.

• The study sample here is college students.
• The dependent variable is motivation and academic achievement, which you can measure with any validated scale (e.g., Intrinsic Motivation Inventory).
• The inclusion criterion for the study’s experimental group is marijuana use.
• The control group might be a group of marijuana non-users from the same population.
• A viable research methodology is to ask both groups to fill out the survey and compare the results.

Step #5: Analyze Your Findings

Once the study is over and you have the collected dataset, it’s time to analyze the findings.

The methodology should also delineate the criteria for proving or disproving the hypothesis.

Using the previous section’s example, your hypothesis is proven if the experimental group reveals lower motivational scores and has a lower GPA . If both groups’ motivation and GPA scores aren’t statistically different, your hypothesis is false.

Step #6: Formulate Your Conclusion

Using your study’s hypothesis and outcomes, you can now generate a conclusion . If the alternative hypothesis is proven, you can conclude that marijuana use hinders students’ achievement and motivation. If the null hypothesis is validated, you should report no identified relationship between low academic achievement and weed use.

Thank you for reading this article! Note that if you need to conduct a business analysis, you can try our free tools: SWOT , VRIO , SOAR , PESTEL , and Porter’s Five Forces .

❓ Research Hypothesis Generator FAQ

❓ what is a research hypothesis.

A hypothesis is a guess or assumption you make by looking at the available data from the natural world. You assume a specific relationship between variables or phenomena and formulate that supposition for further testing with experimentation and analysis.

❓ How to write a hypothesis?

To compose an effective hypothesis, you need to look at your research question and formulate a couple of ways to answer it. The available scientific data can guide you to assume your study’s outcome. Thus, the hypothesis is a guess of how your research question will be answered by the end of your research.

❓ What is the difference between prediction and hypothesis?

A prediction is your forecast about the outcome of some activities or experimentation. It is a guess of what will happen if you perform some actions with a specific object or person. A hypothesis is a more in-depth inquiry into the way things are related. It is more about explaining specific mechanisms and relationships.

❓ What makes a good hypothesis?

A strong hypothesis should indicate the dependent and independent variables, specifying the relationship you assume between them. You can also strengthen your hypothesis by indicating a specific population group, an intervention period, and the context in which you’ll hold the study.

Updated: Aug 23rd, 2024

🔗 References

• What is and How to Write a Good Hypothesis in Research?
• Research questions, hypotheses and objectives – PMC – NCBI
• Developing the research hypothesis – PubMed
• Alternative Hypothesis – SAGE Research Methods
• Alternative Hypothesis Guide: Definition, Types and Examples

Null and Alternative Hypothesis Generator

Take the 4 steps to use this null & alternative hypothesis generator:

• Indicate your research group;
• Add the predicate and the outcome of your study;
• Define the control group if necessary;
• Choose the predicted effect and click “Generate now!”.

Whom or what are you analyzing in your study?

What is the activity or characteristic specific to your research group? The verb should correlate with your research group.

What are you measuring in your study? What thing does the above predicate affect?

Whom or what are you comparing with your research group? This field is optional.

Add here the effect of the predicate on the dependent variable.

Whatever quantitative study you write, you'll surely need to design a null and alternative hypothesis to test with statistical analysis in your study. Don't be scared off by these seemingly complex terms; in fact, formulating these hypotheses may be really fun, especially if you're using our simple, free online tool.

⭐️ Null Hypothesis Generator: the Benefits

• ⚪ How to Use the Tool
• 🔠 Null Vs. Alternative Hypothesis
• 📊 How to Choose between Them

🔗 References

⚪ Null Hypothesis Generator: How to Use It

Let's first clarify how our automated null hypothesis generator can serve your research goals. Its use is an easy and intuitive process that requires little onboarding. Feel free to create a hypothesis for your essay using these steps:

• Indicate the subject of your study (people, processes, or phenomena you're going to examine) – it will be your experimental group.
• Stipulate the activities you expect to measure (that will be the action of your subject).
• Point out the measure (variable) you plan to measure.
• Add a comparison group that will serve as a control for your experimental group.
• Specify the expected effect of the relationship measurement – as we're talking about a null hypothesis here, you should indicate a negative effect.

After you feed that data into the online null hypothesis generator, you will get a well-formulated sentence reflecting your assumed null relationship (that is, an absence of a statistically significant relationship). The same goes for the alternative hypothesis generator, with the only difference in the expectation of a positive effect.

🔠 How to Generate a Null and Alternative Hypothesis

Now it's time to clarify the distinctions between null and alternative hypotheses to give you clear guidance on their formulation.

In other words, these two claims should contradict each other, with one stating that one variable has a visible effect on the other and the second stating that there is no such effect at all.

So, how can you apply these definitions to practice and transform your research question into workable hypotheses?

Here is a handy table with explanations and illustrations of how this happens.

Use this principle for formulating your hypothesis from any other research question you might want to explore. Think of it in the following terms: the null hypothesis stands for no effect, and an alternative hypothesis assumes the existence of that effect.

📊 How to Choose between Null and Alternative Hypothesis

Let's first depart from question about choosing one of the hypotheses, as in most cases, they work in tandem and are inseparable.

So, the good news is that you won't need to choose one of them for your study; they will be presented as a pair of hypotheses. Depending on your study findings, one will be proved, and the other will be disproved.

Now, we have come to the point of using statistics to detect which one is good. In other words, you will need to choose which hypothesis works out and explains the relationship you're examining better than its counterpart. Here are the simple steps you should take to prove and disprove your academic assumptions.

Step 1 - Collect Relevant Data

Once the hypotheses are ready, it's time to check whether the data proves or disproves any of them. Thus, for instance, if you measure the correlation between a person's leadership style and personality type, you should evaluate every respondent's leadership style and personality type with specific quantitative questionnaires.

Step 2 - Use Statistical Analysis

The collected data should be fed into statistical software (e.g., SPSS ) for analysis. You will have a series of quantitative measures for every respondent and every variable neatly organized in rows and lines, assigning specific categories to each number.

Then you can run a t-test or a correlation test depending on the relationship you're studying and see what results you get. Let's talk about the example given above. You will need to run a correlation test for leadership style and personality type measures to see whether the Pearson correlation score is statistically significant.

Step 3 - Reject One Hypothesis & Prove the Other One

Now that you have the statistical analysis results in front of you, it's time to interpret them and reject one of the mutually exclusive hypotheses.

Continuing with the example given above, you will need to see whether your resulting Pearson correlation is high or low:

• Coefficients below 0.5 show a loose correlation;
• 0.5 to 0.7 signify a moderate correlation;
• 0.7-0.9 stands for a high correlation.

Thus, if you see a figure below 0.5, you can consider your null hypothesis proven – there is no significant correlation between leadership style and personality type in the sample of your participants. If your figure is 0.5 and higher, you can consider your alternative hypothesis validated – there is a correlation between a leadership style and a personality type in your chosen sample.

Thank you for reading this article! Try our other free writing tools to prepare and polish any assignment quickly and efficiently.

Updated: Apr 9th, 2024

• When Do You Reject the Null Hypothesis? (With Examples)
• Hypothesis Testing (P-Value Approach) - STAT ONLINE
• What 'Fail to Reject' Means in a Hypothesis Test - ThoughtCo
• Difference between Null Hypothesis and Alternative Hypothesis
• How to Write a Null Hypothesis - Video & Lesson Transcript

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AI Hypothesis Generator

Hypothesis Generator to help you come up with a boilerplate hypothesis for your test ideas. Generate well-structured hypothesis in under 10 seconds!

1. Give us a brief about your hypothesis...

Hypotheses in A/B Testing

Hypotheses form an integral part of A/B Testing. They provide a clear path and expected outcome for the test, based on the initial conditions, such as the user interface and user experience, among others. A well-defined hypothesis is the foundation of any successful A/B test, guiding the direction of the test and serving as a benchmark against which the test’s results are evaluated.

What are the benefits?

The Automated Hypothesis Creator simplifies the first step in the A/B testing process and provides several benefits:

• Quick and efficient hypothesis generation.
• Saves time and resources which can often be invested in analysing the output of the A/B test.
• Provides insightful and scientifically-backed predictions.
• Outlines a clear picture for the A/B test, thus leading to more accurate outcomes.

How to Use it with A/B Testing?

To use the Automated Hypothesis Creator with A/B testing, follow these simple steps:

• Begin by clearly formulating your query.
• Use the text area in the tool to provide the necessary input data.
• Click the “Create Hypothesis” button.
• Wait for a while for the tool to process your request and generate a hypothesis.
• Once the hypothesis is created, use it as a basis for your A/B test.

Try other free tools:

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An AI Tool for Automated Research Question and Hypothesis Generation from a given Scientific Literature

bhaskatripathi/HypothesisHub

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Hypothesishub.

HypothesisHub is an AI Tool for the Automated Generation of Research Questions and Hypotheses from Scientific Literature. It applies a chain of reasoning to scientific literature to generate questions and hypotheses. OpenAI and Langchain serve as the underlying technologies for the tool.

• Generates research questions from a given scientific literature
• Generates a null hypothesis (H0) and an alternate hypothesis (H1) for each research question
• Handles cases where either H0 or H1 is not present
• Automatically generates missing H1 using the LLMChain if needed
• Negates hypothesis statement if H0 is missing

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Please give a star if you like this project and find it useful.

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Create structured research hypotheses

AI Generators in Science and Research

🔬✍️ Formulate precise, well-founded hypotheses for your studies and scientific work. Explore the potential of your research!

Provide additional feedback

Discover the power of a well-formulated hypothesis with our Research Hypothesis Generator. In the world of scientific research, a solid, relevant hypothesis is the foundation on which any study is built.

🧪 Structured and precise

A well-defined hypothesis can guide your experiments and set the course for your discoveries. Our generator provides you with structured proposals based on your field and subject.

🌌 For all areas

Whether you're in biology, physics or the social sciences, we've got you covered. adapted our tool to meet the diversity of research needs.

💭 Refine Your Thinking

With our help, crystallize your idea into a clear, logical hypothesis. Each proposal is designed to stimulate your thinking and enrich your scientific approach.

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Null Hypothesis Generator with Examples

Fill in the fields to get a hypothesis

Add above the person or phenomenon you are focusing on in your study.

Add above the activity or characteristic of your research group). Start with a verb correlating with your subject.

Add above the thing that you are going to measure in your study.

Add above the person or phenomenon you are comparing with your research group.

Add here the effect of the predicate on the dependent variable.

Show Example

Are you looking for a free null hypothesis generator? Writing a hypothesis is important in academic writing since it shows the direction of your research paper. Don’t stress yourself with endless research hours; try our efficient hypothesis generator and get instant results. It is free, simple, and accessible online for students at any academic level. You can formulate a correct hypothesis within minutes, regardless of your paper’s complexity.

• 🤖 How to Use the Tool
• 🧩 What Is a Null Hypothesis

❌ How to Reject a Null Hypothesis

• ❗ References

🤖 Null Hypothesis Generator: How to Use It

A null hypothesis generator is simple to use. You no longer have to write wrong hypotheses because this generator provides accurate results for your research project.

You have to add correct information about your research paper in the provided fields below:

• The subject of your research or experimental group – who or what.
• What the subject or group does – independent variable .
• The measured thing – dependent variable .
• The result.
• The control group (optional).

After filling out the above fields, you can click on the button, and the system will generate results. Ensure you provide accurate information to get relevant results that align with your research question .

🧩 What Is a Null Hypothesis & Why Is It Important?

A null hypothesis is a statement that claims there is no relationship between a dependent and independent variable . The hypothesis is not supposed to show any connection; if it does, the research could have a sampling or experimental error. Thus, a false null hypothesis shows a relationship in the measured observation.

The null hypothesis is vital in research since it determines whether two measured observation subjects are related. It also lets the user know if the outcome is a product of chance or manipulation. However, the hypothesis must be tested to evaluate if it is true or false. The test determines if the null hypothesis should be accepted or rejected.

Researchers often use 2 strategies to test a null hypothesis:

• Significance testing;
• Hypothesis testing.

Both approaches are distinguished based on the observed data. Thus, a null hypothesis is important in research since it will reveal the direction of your essay.

👀 Null Hypothesis Examples

To formulate a null hypothesis, you must drive your statement from a question. Rewrite that question in a different format that presumes there is no relationship between the subjects of observation.

Here are examples of a null hypothesis.

When formulating a null hypothesis, you should always assume that the variables have no relationship. Always start with a question if you want to create a good null hypothesis that reflects your research.

When testing the null hypothesis, the p-value is important in determining the outcome of the observed variables. The p-value in statistics is a number that is calculated from a test. It illustrates the probability of getting the results if the null hypothesis is true.

In short, this value helps researchers decide whether the null hypothesis will be rejected .

Understanding the aspects that lead to the rejection of null hypothesis is essential. The entire process is vital in data analysis , interpretation, and calculations. Besides, you will be able to improve your analytical and research skills in different industries.

Therefore, rejecting a null hypothesis is possible if you follow the falsifiability principle .

What does it mean?

It means that a hypothesis may be regarded as scientifically valid only if it can be tested and proved or disproved based on the resulting data. Therefore, both null and alternative hypotheses should be falsifiable to inform a scholarly inquiry.

So, you must first establish the null hypothesis before testing.

Follow the 4 steps below:

• Establish the hypothesis;
• Create an experimental outline to test the null hypothesis;
• Perform the experiments;
• Interpret the outcome of the investigation.

There are some factors involved when it comes to rejecting a null hypothesis. The p-value is used as an indicator to reject the hypothesis if it is less or equal to the significance level. This level reveals the difference between the test outcome and the null hypothesis.

Therefore, you can use our null hypothesis maker to simplify your work and generate accurate results. Whether you are working on a biology research paper or a statistics paper, understanding how to identify and reject a null hypothesis is important.

We hope the tool and the information were helpful. You are welcome to try our other online writing apps to quickly polish your psychology essay.

❓ Null Hypothesis Generator FAQ

❓ what is a null hypothesis.

A null hypothesis is a statement that claims there is no relationship between independent and independent variables. It is usually based on insufficient evidence that needs more testing to prove if the observed information is true or false.

❓ How to write a null hypothesis?

Writing a null hypothesis requires you to ask a question. You need to rephrase the question in a form that makes no assumptions about the connection between the variables. Formulate the null hypotheses to show the treatment is ineffective.

❓ What does it mean to reject the null hypothesis?

A null hypothesis states that no difference exists between a set of groups. It means that the dependent variable doesn’t have a substantial impact effect on the independent variable. When researchers reject a null hypothesis, they have proven the alternative hypothesis. So, the final result shows there is a relationship between the variables.

❓ What is a null hypothesis example?

An example of a null hypothesis can start with this question: Are adults better at music than children? The null hypothesis, in this case, will state that age doesn’t affect musical ability. Thus, there is no relationship between music and a person’s age.

Updated: Apr 9th, 2024

🔗 References

• Hypothesis Definition & Examples - Simply Psychology
• Hypothesis - APA Dictionary of Psychology
• Why Are Statistics Necessary in Psychology? - Verywell Mind
• Scientific Inquiry Definition: How the Scientific Method Works
• Karl Popper Life & Theory of Falsification - Study.com

Null Hypothesis Examples

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In statistical analysis, the null hypothesis assumes there is no meaningful relationship between two variables. Testing the null hypothesis can tell you whether your results are due to the effect of manipulating ​a dependent variable or due to chance. It's often used in conjunction with an alternative hypothesis, which assumes there is, in fact, a relationship between two variables.

The null hypothesis is among the easiest hypothesis to test using statistical analysis, making it perhaps the most valuable hypothesis for the scientific method. By evaluating a null hypothesis in addition to another hypothesis, researchers can support their conclusions with a higher level of confidence. Below are examples of how you might formulate a null hypothesis to fit certain questions.

What Is the Null Hypothesis?

The null hypothesis states there is no relationship between the measured phenomenon (the dependent variable ) and the independent variable , which is the variable an experimenter typically controls or changes. You do not​ need to believe that the null hypothesis is true to test it. On the contrary, you will likely suspect there is a relationship between a set of variables. One way to prove that this is the case is to reject the null hypothesis. Rejecting a hypothesis does not mean an experiment was "bad" or that it didn't produce results. In fact, it is often one of the first steps toward further inquiry.

To distinguish it from other hypotheses , the null hypothesis is written as ​ H 0  (which is read as “H-nought,” "H-null," or "H-zero"). A significance test is used to determine the likelihood that the results supporting the null hypothesis are not due to chance. A confidence level of 95% or 99% is common. Keep in mind, even if the confidence level is high, there is still a small chance the null hypothesis is not true, perhaps because the experimenter did not account for a critical factor or because of chance. This is one reason why it's important to repeat experiments.

Examples of the Null Hypothesis

To write a null hypothesis, first start by asking a question. Rephrase that question in a form that assumes no relationship between the variables. In other words, assume a treatment has no effect. Write your hypothesis in a way that reflects this.

Other Types of Hypotheses

In addition to the null hypothesis, the alternative hypothesis is also a staple in traditional significance tests . It's essentially the opposite of the null hypothesis because it assumes the claim in question is true. For the first item in the table above, for example, an alternative hypothesis might be "Age does have an effect on mathematical ability."

Key Takeaways

• In hypothesis testing, the null hypothesis assumes no relationship between two variables, providing a baseline for statistical analysis.
• Rejecting the null hypothesis suggests there is evidence of a relationship between variables.
• By formulating a null hypothesis, researchers can systematically test assumptions and draw more reliable conclusions from their experiments.
• What Are Examples of a Hypothesis?
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• What Are the Elements of a Good Hypothesis?
• Scientific Method Vocabulary Terms
• Understanding Simple vs Controlled Experiments
• The Role of a Controlled Variable in an Experiment
• What Is an Experimental Constant?
• What Is a Testable Hypothesis?
• Scientific Hypothesis Examples
• What Is the Difference Between a Control Variable and Control Group?
• DRY MIX Experiment Variables Acronym
• What Is a Controlled Experiment?
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Online Hypothesis Generator

Forge precise, research-backed hypotheses in a snap using our top-notch hypothesis creator, ensuring your study starts on solid ground..

How to Create a Solid & Precise Hypothesis with EssayGPT?

Ever wondered how to come up with a hypothesis that's both detailed and relevant? Kick-start your research endeavors with EssayGPT's hypothesis generator by these steps:

• 1. Start by by indicating the positive or negative trajectory of your hypothesis in the "Effect" section.
• 2. Then, enter specifics of the experimental group in the "Who (what)" field.
• 3. Contrast the experimental group against its counterpart by detailing the control group in the appropriate section.
• 4. Pinpoint the element of study you're measuring by populating the "The measured thing is" field.
• 5. Choose between GPT 3.5 or GPT 4, and hit 'Generate' for your AI-empowered hypotheses.

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Why EssayGPT's Hypothesis Creator Stands Above the Rest?

Embarking on a research venture necessitates precision, clarity, and an unwavering commitment to reliability. EssayGPT  promises all of this and more, setting itself far apart from the competition.

Let’s dive into the unparalleled features of our hypothesis generator:

AI-Powered Precision: Central to the EssayGPT's hypothesis generator is an avant-garde AI framework. This ensures every hypothesis generated is data-driven, accurate, and aligns with your specified parameters.

Swift, On-Point Outputs: Time is of the essence in research. EssayGPT's hypothesis generator pledges quick turnarounds, without compromising the quality and relevance of the generated hypotheses.

Diverse Subject Mastery: From social sciences to intricate physics postulations, EssayGPT's hypothesis generator extends its prowess across a plethora of disciplines, ensuring your topic, no matter how niche, finds its rightful hypothesis.

A Breeze of Usability: Ditch convoluted interfaces. EssayGPT's hypothesis generator boasts an intuitive design for all users, making hypothesis crafting as effortless as a couple of clicks.

Key Steps on Writing Proper Research Hypothesis with EssayGPT

Tapping into the potential of EssayGPT's hypothesis generator can revolutionize your research process. However, to optimize the AI's capabilities, a few key considerations can significantly enhance the coherence and relevance of the generated hypotheses.

Here's a deeper dive into those nuances.

Precision in Input: The tool's prowess lies in its ability to interpret and process the information it's given. Just as a finely tuned instrument delivers the best music, clear and specific inputs allow the generator to produce accurate hypotheses. Being vague or too broad might lead to generic outcomes that don’t precisely serve your research aims.

Alignment with Research Context: The essence of a valuable hypothesis is its seamless fit within the broader research landscape. It's not just about a statement, but one that directly speaks to, and illuminates, the research problem or question you're addressing. By ensuring that the generated hypothesis aligns contextually, you guarantee its relevance and applicability.

Vocabulary Matters: Each field of study has its lexicon. Incorporating field-specific terms or jargon can transform a generic statement into a specialized hypothesis. It’s not just about linguistic accuracy, but about imbuing your hypothesis with the depth and resonance pertinent to your study's discipline.

The Human Element: AI is a powerful tool, but it's the human touch that brings depth, intuition, and context. After the AI crafts the hypothesis, it's beneficial to weave in personal insights or adjust nuances. This ensures that while the hypothesis is technically sound, it also captures the unique intricacies and flavors of individual research endeavors.

Iconic Features of EssayGPT's Hypothesis Maker at a Glance

Check Out Other Powerful AI Tools Just Like This Hypothesis Generator

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1. Can EssayGPT's hypothesis creator tackle complex and multidimensional topics?

Absolutely. The hypothesis creator harnesses a state-of-the-art AI algorithm, expertly designed to navigate even the most complex and multidimensional subjects. Leveraging advanced contextual comprehension coupled with vast datasets, the tool is adept at crafting accurate hypotheses irrespective of topic intricacy.

2. Are users expected to incur any costs when using EssayGPT's Hypothesis maker?

The basic version of the hypothesis generator is free and permits users to generate content up to 3,000 words per week. For users requiring more extensive capabilities, we offer subscription plans that provide increased word limits and access to our advanced content generation features.

3. Does the EssayGPT hypothesis generator offer support for multiple languages?

Certainly! EssayGPT's esteemed hypothesis generator is linguistically versatile, offering compatibility with an impressive roster of over 30 languages. This ensures that your research endeavors remain unhindered, irrespective of the language of preference.

4. How does EssayGPT's hypothesis generator ensure the uniqueness of the generated hypothesis?

Ensuring that your hypotheses are both pristine and unparalleled is at the heart of EssayGPT's ethos. To this end, our hypothesis generator taps into cutting-edge language models to ensure that every hypothesis sculpted retains an aura of unmatched originality.

Use Our Hypothesis Generator to Power Your Research Journey

Try EssayGPT's Hypothesis Generator to explore new frontiers. Formulate testable hypotheses to supercharge your research!

Online Hypothesis Generator

Add the required information into the fields below to build a list of well-formulated hypotheses.

• If patients follow medical prescriptions, then their condition will improve.
• If patients follow medical prescriptions, then their condition will show better results.
• If patients follow medical prescriptions, then their condition will show better results than those who do not follow medical prescriptions.
• H0 (null hypothesis) - Attending most lectures by first-year students has no effect on their exam scores.
• H1 (alternative hypothesis) - Attending most lectures by first-year students has a positive effect on their exam scores.

* Hint - choose either null or alternative hypothesis

⭐️ Hypothesis Creator: the Benefits

• 🔎 How to Use the Tool?
• 🤔 What Is a Hypothesis?
• 👣 Steps to Generating a Hypothesis
• 🔍 References

🔎 Hypothesis Generator: How to Use It?

The generation of a workable hypothesis is not an easy task for many students. You need to research widely, understand the gaps in your study area, and comprehend the method of hypothesis formulation to the dot. Lucky for you, we have a handy hypothesis generator that takes hours of tedious work out of your study process.

To use our hypothesis generator, you’ll need to do the following:

• Indicate your experimental group (people, phenomena, event)
• Stipulate what it does
• Add the effect that the subject’s activities produce
• Specify the comparison group

Once you put all this data into our online hypothesis generator, click on the “Generate hypothesis” tab and enjoy instant results. The tool will come up with a well-formulated hypothesis in seconds.

🤔 What Is a Research Hypothesis?

A hypothesis is a claim or statement you make about the assumed relationship between the dependent and independent variables you're planning to test. It is formulated at the beginning of your study to show the direction you will take in the analysis of your subject of interest.

The hypothesis works in tandem with your research purpose and research question , delineating your entire perspective.

For example, if you focus on the quality of palliative care in the USA , your perspective may be as follows.

This way, your hypothesis serves as a tentative answer to your research question, which you aim to prove or disprove with scientific data, statistics, and analysis.

Hypothesis Types

In most scholarly studies, you’ll be required to write hypotheses in pairs – as a null and alternative hypothesis :

• The alternative hypothesis assumes a statistically significant relationship between the identified variables. Thus, if you find that relationship in the analysis process, you can consider the alternative hypothesis proven.
• A null hypothesis is the opposite; it assumes that there is no relationship between the variables. Thus, if you find no statistically significant association, the null hypothesis is considered proven.

A handy example is as follows:

You are researching the impact of sugar intake on child obesity. So, based on your data, you can either find that the number of sugar spoons a day directly impacts obesity or that the sugar intake is not associated with obesity in your sample. The hypotheses for this study would be as follows:

ALTERNATIVE

There is a relationship between the number of sugar spoons consumed daily and obesity in U.S. preschoolers.

There is no relationship between the number of sugar spoons consumed daily and obesity in U.S. preschoolers.

Besides, hypotheses can be directional and non-directional by type:

• A directional hypothesis assumes a cause-and-effect relationship between variables, clearly designating the assumed difference in study groups or parameters.
• A non-directional hypothesis , in turn, only assumes a relationship or difference without a clear estimate of its direction.

NON-DIRECTIONAL

Students in high school and college perform differently on critical thinking tests.

DIRECTIONAL

College students perform better on critical thinking tests that high-school students.

👣 How to Make a Hypothesis in Research

Now let’s cover the algorithm of hypothesis generation to make this process simple and manageable for you.

Step #1: Formulate Your Research Question

The first step is to create a research question . Study the topic of interest and clarify what aspect you're fascinated about, wishing to learn more about the hidden connections, effects, and relationships.

Step #2: Research the Topic

Next, you should conduct some research to test your assumption and see whether there’s enough published evidence to back up your point. You should find credible sources that discuss the concepts you’ve singled out for the study and delineate a relationship between them. Once you identify a reasonable body of research, it’s time to go on.

Step #3: Make an Assumption

With some scholarly data, you should now be better positioned to make a researchable assumption.

For instance, if you find out that many scholars associate heavy social media use with a feeling of loneliness, you can hypothesize that the hours spent on social networks will directly correlate with perceived loneliness intensity.

Step #4: Improve Your Hypothesis

Now that you have a hypothesis, it’s time to refine it by adding context and population specifics. Who will you study? What social network will you focus on? In this example, you can focus on the student sample’s use of Instagram .

Step #5: Try Different Phrasing

The final step is the proper presentation of your hypothesis. You can try several variants, focusing on the variables, correlations , or groups you compare.

For instance, you can say that students spending 3+ hours on Instagram every day are lonelier than their peers. Otherwise, you can hypothesize that heavy social media use leads to elevated feelings of loneliness.

👀 Null Hypothesis Examples

If you’re unsure about how to generate great hypotheses, get some inspiration from the list of examples formulated by our writing pros.

Thank you for reading this article! If you’re planning to analyze business issues, try our free templates: PEST , PESTEL , SWOT , SOAR , VRIO , and Five Forces .

❓ Hypothesis Generator FAQ

❓ what does hypothesis mean.

A hypothesis in an essay or a larger research assignment is your claim or prediction of the relationship you assume between the identified dependent and independent variables. You share an assumption that you’re going to test with research and data analysis in the later sections of your paper.

❓ How to create a hypothesis?

The first step to formulating a good hypothesis is to ask a question about your subject of interest and understand what effects it may experience from external sources or how it changes over time. You can identify differences between groups and inquire into the nature of those distinctions. In any way, you need to voice some assumption that you’ll further test with data; that assumption will be your hypothesis for a study.

❓ What is a null and alternative hypothesis?

You need to formulate a null and alternative hypothesis if you plan to test some relationship between variables with statistical instruments. For example, you might compare a group of students on an emotional intelligence scale to determine whether first-year students are less emotionally competent than graduates. In this case, your alternative hypothesis would state that they are, and a null hypothesis would say that there is no difference between student groups.

❓ What does it mean to reject the null hypothesis?

A null hypothesis assumes that there is no difference between groups or that the dependent variables don't have any sizable impact on the independent variable. If your null hypothesis gets rejected, it means that your alternative hypothesis has been proved, showing that there is a tangible difference or relationship between your variables.

🔗 References

• How to Write a Hypothesis in 6 Steps - Grammarly
• The Hypothesis in Science Writing
• Hypothesis Definition & Examples - Simply Psychology
• Hypothesis Examples: Different Types in Science and Research
• Forming a Good Hypothesis for Scientific Research

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Writing Null Hypotheses in Research and Statistics

Last Updated: September 2, 2024 Fact Checked

This article was co-authored by Joseph Quinones and by wikiHow staff writer, Jennifer Mueller, JD . Joseph Quinones is a Physics Teacher working at South Bronx Community Charter High School. Joseph specializes in astronomy and astrophysics and is interested in science education and science outreach, currently practicing ways to make physics accessible to more students with the goal of bringing more students of color into the STEM fields. He has experience working on Astrophysics research projects at the Museum of Natural History (AMNH). Joseph recieved his Bachelor's degree in Physics from Lehman College and his Masters in Physics Education from City College of New York (CCNY). He is also a member of a network called New York City Men Teach. There are 7 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 29,512 times.

Are you working on a research project and struggling with how to write a null hypothesis? Well, you've come to the right place! Keep reading to learn everything you need to know about the null hypothesis, including a review of what it is, how it relates to your research question and your alternative hypothesis, as well as how to use it in different types of studies.

Things You Should Know

• Write a research null hypothesis as a statement that the studied variables have no relationship to each other, or that there's no difference between 2 groups.

• Adjust the format of your null hypothesis to match the statistical method you used to test it, such as using "mean" if you're comparing the mean between 2 groups.

What is a null hypothesis?

• Research hypothesis: States in plain language that there's no relationship between the 2 variables or there's no difference between the 2 groups being studied.
• Statistical hypothesis: States the predicted outcome of statistical analysis through a mathematical equation related to the statistical method you're using.

Examples of Null Hypotheses

Null Hypothesis vs. Alternative Hypothesis

• For example, your alternative hypothesis could state a positive correlation between 2 variables while your null hypothesis states there's no relationship. If there's a negative correlation, then both hypotheses are false.

• You need additional data or evidence to show that your alternative hypothesis is correct—proving the null hypothesis false is just the first step.
• In smaller studies, sometimes it's enough to show that there's some relationship and your hypothesis could be correct—you can leave the additional proof as an open question for other researchers to tackle.

How do I test a null hypothesis?

• Group means: Compare the mean of the variable in your sample with the mean of the variable in the general population. [6] X Research source
• Group proportions: Compare the proportion of the variable in your sample with the proportion of the variable in the general population. [7] X Research source
• Correlation: Correlation analysis looks at the relationship between 2 variables—specifically, whether they tend to happen together. [8] X Research source
• Regression: Regression analysis reveals the correlation between 2 variables while also controlling for the effect of other, interrelated variables. [9] X Research source

Templates for Null Hypotheses

• Research null hypothesis: There is no difference in the mean [dependent variable] between [group 1] and [group 2].

• Research null hypothesis: The proportion of [dependent variable] in [group 1] and [group 2] is the same.

• Research null hypothesis: There is no correlation between [independent variable] and [dependent variable] in the population.

• Research null hypothesis: There is no relationship between [independent variable] and [dependent variable] in the population.

Expert Q&A

You Might Also Like

Expert Interview

Thanks for reading our article! If you’d like to learn more about physics, check out our in-depth interview with Joseph Quinones .

• ↑ https://online.stat.psu.edu/stat100/lesson/10/10.1
• ↑ https://online.stat.psu.edu/stat501/lesson/2/2.12
• ↑ https://support.minitab.com/en-us/minitab/21/help-and-how-to/statistics/basic-statistics/supporting-topics/basics/null-and-alternative-hypotheses/
• ↑ https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5635437/
• ↑ https://online.stat.psu.edu/statprogram/reviews/statistical-concepts/hypothesis-testing
• ↑ https://education.arcus.chop.edu/null-hypothesis-testing/
• ↑ https://sphweb.bumc.bu.edu/otlt/mph-modules/bs/bs704_hypothesistest-means-proportions/bs704_hypothesistest-means-proportions_print.html

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Use Our Free A/B Testing Hypothesis Generator . Never Miss Key Elements From Your Hypotheses. Get Big Conversion Lifts.

Observation, inadvertent impact.

Streamline Your Hypothesis Generation Research with Custom Templates the Pros Use.

Have questions about a/b testing hypotheses, what is a hypothesis.

Many people define a hypothesis as an “educated guess”.

To be more precise, a properly constructed hypothesis predicts a possible outcome to an experiment or a test where one variable (the independent one ) is tweaked and/or modified and the impact is measured by the change in behavior of another variable (generally the dependent one).

A hypothesis should be specific (it should clearly define what is being altered and what is the expected impact), data-driven (the changes being made to the independent variable should be based on historic data or theories that have been proven in the past), and testable (it should be possible to conduct the proposed test in a controlled environment to establish the relationship between the variables involved, and disprove the hypothesis - should it be untrue.)

What is the Cost of a Hastily Assembled Hypothesis?

According to an analysis of over 28,000 tests run using the Convert Experiences platform, only 1 in 5 tests proves to be statistically significant.

While more and more debate is opening up around sticking to the concept of 95% statistical significance, it is still a valid rule of thumb for optimizers who do not want to get into the fray with peeking vs. no peeking, and custom stopping rules for experiments.

There might be a multitude of reasons why a test does not reach statistical significance. But framing a tenable hypothesis that already proves itself logistically feasible on paper is a better starting point than a hastily assembled assumption.

Moreover, the aim of an A/B test may be to extract a learning, but some learnings come with heavy costs. 26% decrease in conversion rates to be specific.

A robust hypothesis may not be the answer to all testing woes, but it does help prioritisation of possible solutions and leads testing teams to pick low hanging fruits.

How is an A/B Testing Hypothesis Different?

An A/B test should be treated with the same rigour as tests conducted in laboratories. That is an easy way to guarantee better hypotheses, more relevant experiments, and ultimately more profitable optimization programs.

The focus of an A/B test should be on first extracting a learning , and then monetizing it in the form of increased registration completions, better cart conversions and more revenue.

If that is true, then an A/B test hypothesis is not very different from a regular scientific hypothesis. With a couple of interesting points to note:

• Most scientific hypotheses proceed with one independent variable and one dependent variable, for the sake of simplicity. But in A/B tests, there might be changes made to several independent variables at the same time. Under such circumstances it is good to explore the relationship between the independent variables to make sure that they do not inadvertently impact one another. For example changing both the value proposition and button copy of a landing page to determine improvement in click through or completion rates is tricky. Reaching a point where the browser is compelled to click the button could easily have been impacted by the value proposition (as in a strong hook and heading). So what caused the improvement in the dependent variable? Was it the change to the first element or the second one?
• The concept of Operational Definition is non-negotiable in most laboratory experiments. And comes baked with the question of ethics or morality. Operation Definition is the specific process that will be used to quantify the change in the value/behavior of the independent variable in the test. As an example, if a test wishes to measure the level of frustration that subjects experience when they are exposed to certain stimuli, researchers must be careful to define exactly how they will measure the output or frustration. Should they allow the test subjects to act out, in which case they may hurt or harm other individuals. Or should they use a non-invasive technique like an fMRI scan to monitor brain activity and collect the needed data. In A/B tests however, since data is collected through relatively inanimate channels like analytics dashboards, generally little thought is spared to Operational Definition and the impact of A/B testing on the human subjects (site traffic in this case).

The 5 Essential Parts of an A/B Testing Hypothesis

A robust A/B testing hypothesis should be assembled in 5 key parts:

1. OBSERVATION

This includes a clear outline of the problem (the unexplained phenomenon) observed and what it entails. This section should be completely free of conjecture and rely solely on good quality data - either qualitative and/or quantitative - to bring a potential area of improvement to light. It also includes a mention of the way in which the data is collected.

Proper observation ensures a credible hypothesis that is easy to “defend” later down the line.

2. EXECUTION

This is the where, what, and the who of the A/B test. It specifies the change(s) you will be making to site element(s) in an attempt to solve the problem that has been outlined under “OBSERVATION”. It serves to also clearly define the segment of site traffic that will be exposed to the experiment.

Proper execution guidelines set the rhythm for the A/B test. They define how easy or difficult it will be to deploy the test and thus aid hypothesis prioritization .

This is where you make your educated guess or informed prediction. Based on a diligently identified OBSERVATION and EXECUTION guidelines that are possible to deploy, your OUTCOME should clearly mention two things:

• The change (increase or decrease) you expect to see to the problem or the symptoms of the problem identified under OBSERVATION.
• The Key Performance Indicators (KPIs) you will be monitoring to gauge whether your prediction has panned out, or not.

In general most A/B tests have one primary KPI and a couple of secondary KPIs or ways to measure impact. This is to ensure that external influences do not skew A/B test results and even if the primary KPI is compromised in some way, the secondary KPIs do a good job of indicating that the change is indeed due to the implementation of the EXECUTION guidelines, and not the result of unmonitored external factors.

4. LOGISTICS

An important part of hypothesis formulation, LOGISTICS talk about what it will take to collect enough clean data from which a reliable conclusion can be drawn. How many unique tested visitors, what is the statistical significance desired, how many conversions is enough and what is the duration for which the A/B test should run? Each question on its own merits a blog or a lesson. But for the sake of convenience, Convert has created a Free Sample Size & A/B/N Test Duration Calculator .

Set the right logistical expectations so that you can prioritise your hypotheses for maximum impact and minimum effort .

5. INADVERTENT IMPACT

This is a nod in the direction of ethics in A/B testing and marketing, because experiments involve humans and optimizers should be aware of the possible impact on their behavior.

Often a thorough analysis at this stage can modify the way impact is measured or an experiment is conducted. Or Convert certainly hopes that this will be the case in future. Here’s why ethics do matter in testing.

Now Organize, Prioritise & Learn from Your Hypotheses.

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Methodology

• How to Write a Strong Hypothesis | Steps & Examples

How to Write a Strong Hypothesis | Steps & Examples

Published on May 6, 2022 by Shona McCombes . Revised on November 20, 2023.

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 .

Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

Table of contents

What is a hypothesis, developing a hypothesis (with example), hypothesis examples, other interesting articles, 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 types of variables .

• An independent variable is something the researcher changes or controls.
• A dependent variable is something the researcher observes and measures.

If there are any control variables , extraneous variables , or confounding variables , be sure to jot those down as you go to minimize the chances that research bias  will affect your results.

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 .

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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 ensure that you’re embarking on a relevant topic . This can also help you identify which variables you will study and what you think the relationships are between them. Sometimes, you’ll have to operationalize 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.

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

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.

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 .

• H 0 : The number of lectures attended by first-year students has no effect on their final exam scores.
• H 1 : The number of lectures attended by first-year students has a positive effect on their final exam scores.

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

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

Prevent plagiarism. Run a free check.

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.

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.

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McCombes, S. (2023, November 20). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved September 4, 2024, from https://www.scribbr.com/methodology/hypothesis/

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• Null and Alternative Hypotheses | Definitions & Examples

Null and Alternative Hypotheses | Definitions & Examples

Published on 5 October 2022 by Shaun Turney . Revised on 6 December 2022.

The null and alternative hypotheses are two competing claims that researchers weigh evidence for and against using a statistical test :

• Null hypothesis (H 0 ): There’s no effect in the population .
• Alternative hypothesis (H A ): There’s an effect in the population.

The effect is usually the effect of the independent variable on the dependent variable .

Table of contents

Answering your research question with hypotheses, what is a null hypothesis, what is an alternative hypothesis, differences between null and alternative hypotheses, how to write null and alternative hypotheses, frequently asked questions about null and alternative hypotheses.

The null and alternative hypotheses offer competing answers to your research question . When the research question asks “Does the independent variable affect the dependent variable?”, the null hypothesis (H 0 ) answers “No, there’s no effect in the population.” On the other hand, the alternative hypothesis (H A ) answers “Yes, there is an effect in the population.”

The null and alternative are always claims about the population. That’s because the goal of hypothesis testing is to make inferences about a population based on a sample . Often, we infer whether there’s an effect in the population by looking at differences between groups or relationships between variables in the sample.

You can use a statistical test to decide whether the evidence favors the null or alternative hypothesis. Each type of statistical test comes with a specific way of phrasing the null and alternative hypothesis. However, the hypotheses can also be phrased in a general way that applies to any test.

The null hypothesis is the claim that there’s no effect in the population.

If the sample provides enough evidence against the claim that there’s no effect in the population ( p ≤ α), then we can reject the null hypothesis . Otherwise, we fail to reject the null hypothesis.

Although “fail to reject” may sound awkward, it’s the only wording that statisticians accept. Be careful not to say you “prove” or “accept” the null hypothesis.

Null hypotheses often include phrases such as “no effect”, “no difference”, or “no relationship”. When written in mathematical terms, they always include an equality (usually =, but sometimes ≥ or ≤).

Examples of null hypotheses

The table below gives examples of research questions and null hypotheses. There’s always more than one way to answer a research question, but these null hypotheses can help you get started.

*Note that some researchers prefer to always write the null hypothesis in terms of “no effect” and “=”. It would be fine to say that daily meditation has no effect on the incidence of depression and p 1 = p 2 .

The alternative hypothesis (H A ) is the other answer to your research question . It claims that there’s an effect in the population.

Often, your alternative hypothesis is the same as your research hypothesis. In other words, it’s the claim that you expect or hope will be true.

The alternative hypothesis is the complement to the null hypothesis. Null and alternative hypotheses are exhaustive, meaning that together they cover every possible outcome. They are also mutually exclusive, meaning that only one can be true at a time.

Alternative hypotheses often include phrases such as “an effect”, “a difference”, or “a relationship”. When alternative hypotheses are written in mathematical terms, they always include an inequality (usually ≠, but sometimes > or <). As with null hypotheses, there are many acceptable ways to phrase an alternative hypothesis.

Examples of alternative hypotheses

The table below gives examples of research questions and alternative hypotheses to help you get started with formulating your own.

Null and alternative hypotheses are similar in some ways:

• They’re both answers to the research question
• They both make claims about the population
• They’re both evaluated by statistical tests.

However, there are important differences between the two types of hypotheses, summarized in the following table.

To help you write your hypotheses, you can use the template sentences below. If you know which statistical test you’re going to use, you can use the test-specific template sentences. Otherwise, you can use the general template sentences.

The only thing you need to know to use these general template sentences are your dependent and independent variables. To write your research question, null hypothesis, and alternative hypothesis, fill in the following sentences with your variables:

Does independent variable affect dependent variable ?

• Null hypothesis (H 0 ): Independent variable does not affect dependent variable .
• Alternative hypothesis (H A ): Independent variable affects dependent variable .

Test-specific

Once you know the statistical test you’ll be using, you can write your hypotheses in a more precise and mathematical way specific to the test you chose. The table below provides template sentences for common statistical tests.

Note: The template sentences above assume that you’re performing one-tailed tests . One-tailed tests are appropriate for most studies.

The null hypothesis is often abbreviated as H 0 . When the null hypothesis is written using mathematical symbols, it always includes an equality symbol (usually =, but sometimes ≥ or ≤).

The alternative hypothesis is often abbreviated as H a or H 1 . When the alternative hypothesis is written using mathematical symbols, it always includes an inequality symbol (usually ≠, but sometimes < or >).

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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Turney, S. (2022, December 06). Null and Alternative Hypotheses | Definitions & Examples. Scribbr. Retrieved 3 September 2024, from https://www.scribbr.co.uk/stats/null-and-alternative-hypothesis/

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Free Essay Hypothesis Generator

Writing an essay hypothesis might be challenging: it has to be well-structured and follow specific standards. But we have a solution! Our free essay hypothesis generator is here to help you. Check it out and take your writing to the next level!

• If high school students receive sex education, then their ability to prevent unwanted pregnancy will improve as compared to those who do not receive sex education.
• If high school students receive sex education, then their ability to prevent unwanted pregnancy will show better results than those who do not receive sex education.
• H0 (null hypothesis) - If high school students receive sex education, it has no effect on their ability to prevent unwanted pregnancy as compared to those who do not receive sex education.
• H1 (alternative hypothesis) - If high school students receive sex education, it has a negative effect on their ability to prevent unwanted pregnancy as compared to those who do not receive sex education.
• If high school students receive sex education, then their ability to prevent unwanted pregnancy will worsen as compared to those who do not receive sex education.
• If high school students receive sex education, then their ability to prevent unwanted pregnancy will show worse results than those who do not receive sex education.
• H1 (alternative hypothesis) - If high school students receive sex education, it has a positive effect on their ability to prevent unwanted pregnancy as compared to those who do not receive sex education.
• ✅ Why Use Our Generator?
• 🤔 What Is an Essay Hypothesis?
• ✍️ How to Write a Hypothesis?
• ✨ Hypothesis Examples

👌 Hypothesis Maker: the Benefits

🔗 references, ✅ why use our essay hypothesis generator.

We are sure you will enjoy using Overnight Essay's essay hypothesis generator. Check out its awesome benefits:

🤔 Null and Alternative Hypothesis

An essay hypothesis is a claim that predicts the outcome of your research and tests the relationship between two variabilities . Your research can either prove or disprove it.

Like a thesis statement, an essay hypothesis is an answer to your research question. However, there is a difference:

• A hypothesis shows your ability to make a logical assumption. It can be supported by observations, statistical analysis, experiments, or other scientific research methods. It's usually used for quantitative analysis .
• A thesis statement defines your research and sums up its main points. We can use it for both quantitative and qualitative analysis. A thesis can be formulated manually or generated automatically .

Components of a Hypothesis

To write a solid hypothesis, you should define your variables first. There are two types of them: independent and dependent :

• An independent variable can be controlled by a researcher during an experiment.
• A dependent variable can only be measured and observed.

Let’s take a closer look.

Suppose your research is about the effect of having pets on mental well-being. Your hypothesis might be:

Spending more time playing with your pet positively affects one's mental health.

Here, the amount of time spent playing with a pet is an independent variable because this is something we can change and control. Therefore, the positive effect is the dependable variable since we can only observe it.

Types of Hypotheses

A hypothesis may vary depending on the goal and nature of your research. So, let’s break down several types of them.

• A statistical hypothesis tests a limited sample of a population . It uses statistics to calculate the result.
• A simple hypothesis tests a relationship between two variables and predicts the potential result of the research.
• An empirical or working hypothesis is based on factual data. It is used to create a theory for testing .
• A complex hypothesis tests a relationship between two or more dependent or independent variables.
• A logical hypothesis predicts the result of your research with no evidence or actual data but based on deduction.
• A null hypothesis is created to show that there is no relationship between variables. It is abbreviated as H0.
• An alternative hypothesis disproves a null hypothesis and states the opposite. It is abbreviated as H1 or HA.

✍️ How to Make a Hypothesis for an Essay

So, now you know what a hypothesis is. But how exactly do you write it? Here’s a step-by-step process.

Knowing the hypothesis will help you create an outline and topic sentences for your paper.

✨ Good Essay Hypothesis Examples

To understand what an essay hypothesis should be like, check out the examples below and see what makes them good.

We hope this article was helpful for you. Check out our essay hypothesis generator, topic generator , sentence rephraser , and other tools. Good luck with your studies!

❓ Hypothesis Maker FAQ

📍 how do you write a hypothesis for an essay, 📍 what is an example of a hypothesis, 📍 what are the 3 types of hypotheses.

• A simple hypothesis introduces a relationship between an independent and dependent variable.
• A complex one includes the relationship between two or more variables.
• Finally, a directional hypothesis includes the direction of the expected result.

📍 How to introduce a hypothesis in an essay?

• How to Write a Hypothesis: Grammarly
• Research Hypothesis: Oakland University
• How to Write a Hypothesis to an Analytical Essay: Classroom
• What Is the Difference Between a Thesis Statement and a Hypothesis Statement?: American Public University System

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