Hypothesis Generator

Predicted direction of the dependent variable

How to Use the Hypothesis Generator

1. Name the independent variable. This is what you change or compare, written as a measurable thing: hours of sleep per night.
2. Name the dependent variable. This is what you measure to see the effect: test scores. Add a population, such as high school students, if your claim is about a particular group.
3. Choose the predicted direction. Increase, Decrease or Change (either way) describes what you expect to happen to the dependent variable.
4. Press Generate Hypotheses and edit. Four forms appear, each with a Copy button. Adjust the grammar and define each variable precisely before you use one.

The Four Forms

Worked Example

Enter hours of sleep per night as the independent variable, test scores as the dependent variable, high school students as the population, and leave the direction on Increase. The tool returns four statements:

• If/then: If hours of sleep per night is changed, then test scores will increase among high school students.
• Directional (H1): A change in hours of sleep per night will lead to an increase in test scores among high school students.
• Non-directional (H1): There is a relationship between hours of sleep per night and test scores among high school students.
• Null (H0): There is no relationship between hours of sleep per night and test scores among high school students; any observed difference in test scores is due to chance.

These are frames, so read each one aloud. “Hours … is changed” should be “are changed”, and you can make the cause concrete: “If students sleep an extra hour a night, then their mean test score will rise.” With Change (either way) selected, the directional form reads “a measurable change”, which is the non-directional claim in different words; use the non-directional form in that case.

Hypothesis, Prediction and Research Question

A research question asks what you want to find out (“Does sleep affect test scores?”). A hypothesis is a testable answer to it, stated about variables. The null hypothesis is the version a test tries to reject: significance tests ask how surprising your data would be if H0 were true, and you either reject H0 or fail to reject it. Nothing is ever “proven”. For the next step after you write it, use the Sample Size Calculator and then the T-Test Calculator or P-Value Calculator once you have data.

What Makes a Hypothesis Testable

• Both variables must be measurable. Replace vague terms with things you can count or score. 'Better focus' is not measurable; 'score on a 10-minute attention task' is. If you cannot name the instrument or unit, the hypothesis is not ready to test.
• It must be falsifiable. A good hypothesis can be proven wrong by data. If no possible result would count against your claim, it is not a scientific hypothesis — it is an opinion. The null hypothesis (H0) exists precisely so your test has something to reject.
• Define the population. An effect found in college students may not hold for children or older adults. Naming the population keeps your claim honest about who your results apply to, and tells readers how far the findings generalize.
• Change one variable at a time. If you manipulate two things at once, you cannot tell which caused the effect. Keep one independent variable per hypothesis and hold everything else constant — that is what makes the comparison fair.

Which Tool Do You Need?

• Variables to hypotheses: this page.
• A topic to research questions: Research Question Generator; clinical questions in PICO form, PICO Question Generator.
• Questions to put to participants: Survey Question Generator.
• An argument for an essay rather than an experiment: Thesis Statement Generator.

Frequently Asked Questions

What is the difference between the independent and dependent variable?

The independent variable is what you change or manipulate in the study — the suspected cause. The dependent variable is what you measure to see the effect. In 'Does sleep affect test scores?', hours of sleep is the independent variable and test score is the dependent variable.

What are H0 and H1?

H0 is the null hypothesis: it states there is no effect or no relationship between your variables, and it is what statistical tests actually test against. H1 (the alternative hypothesis) states there is an effect. Research never proves H1 directly — it collects evidence that lets you reject or fail to reject H0.

What is the difference between a directional and non-directional hypothesis?

A directional hypothesis predicts which way the effect goes — for example, that scores will increase. A non-directional hypothesis predicts only that a relationship exists, without specifying the direction. Use a directional hypothesis when prior research gives you a reason to expect a particular direction; otherwise, non-directional is the safer claim.

Does this tool use AI to write my hypothesis?

No. It slots your variables into the standard hypothesis formats used in research methods courses — if/then, directional, non-directional, and null. The scientific thinking is still yours: the tool only handles the phrasing conventions, and you should refine the wording so each variable is precisely defined.

How do I write a hypothesis?

Name your two variables in measurable terms, say how you expect the independent variable to affect the dependent one, and name the group you are studying. Write it so that data could show it to be wrong. The generator gives you that wording in four forms to edit.