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- 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 December 2, 2022.

## Example: Hypothesis

Daily apple consumption leads to fewer doctor’s visits.

## Table of contents

## 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.

## Step 1. Ask a question

## Step 2. Do some preliminary research

## Step 3. Formulate your hypothesis

## 4. Refine your hypothesis

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

## 5. Phrase your hypothesis in three ways

## 6. Write a null hypothesis

- 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.

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## Cite this Scribbr article

McCombes, S. (2022, December 02). How to Write a Strong Hypothesis | Steps & Examples. Scribbr. Retrieved February 28, 2023, from https://www.scribbr.com/methodology/hypothesis/

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## Keyboard Shortcuts

The general idea of hypothesis testing involves:

- Making an initial assumption.
- Collecting evidence (data).
- Based on the available evidence (data), deciding whether to reject or not reject the initial assumption.

## Example S.3.1

Is normal body temperature really 98.6 degrees f section .

- If it is likely , then the researcher does not reject his initial assumption that the average adult body temperature is 98.6 degrees. There is not enough evidence to do otherwise.
- either the researcher's initial assumption is correct and he experienced a very unusual event;
- or the researcher's initial assumption is incorrect.

## Example S.3.2

Criminal trial analogy section .

In statistics, the data are the evidence.

The jury then makes a decision based on the available evidence:

- If the jury finds sufficient evidence — beyond a reasonable doubt — to make the assumption of innocence refutable, the jury rejects the null hypothesis and deems the defendant guilty. We behave as if the defendant is guilty.
- If there is insufficient evidence, then the jury does not reject the null hypothesis . We behave as if the defendant is innocent.

## Errors in Hypothesis Testing Section

- If we reject the null hypothesis, we do not prove that the alternative hypothesis is true.
- If we do not reject the null hypothesis, we do not prove that the null hypothesis is true.

Let's review the two types of errors that can be made in criminal trials:

Table S.3.2 shows how this corresponds to the two types of errors in hypothesis testing.

## Making the Decision Section

- We could take the " critical value approach " (favored in many of the older textbooks).
- Or, we could take the " P -value approach " (what is used most often in research, journal articles, and statistical software).

## In Practice

- We would want to conduct the first hypothesis test if we were interested in concluding that the average grade point average of the group is more than 3.
- We would want to conduct the second hypothesis test if we were interested in concluding that the average grade point average of the group is less than 3.
- And, we would want to conduct the third hypothesis test if we were only interested in concluding that the average grade point average of the group differs from 3 (without caring whether it is more or less than 3).

## Introduction to Hypothesis Testing

A statistical hypothesis is an assumption about a population parameter .

For example, we may assume that the mean height of a male in the U.S. is 70 inches.

## The Two Types of Statistical Hypotheses

There are two types of statistical hypotheses:

## Hypothesis Tests

A hypothesis test consists of five steps:

2. Determine a significance level to use for the hypothesis.

Decide on a significance level. Common choices are .01, .05, and .1.

4. Reject or fail to reject the null hypothesis.

Interpret the results of the hypothesis test in the context of the question being asked.

## The Two Types of Decision Errors

There are two types of decision errors that one can make when doing a hypothesis test:

## One-Tailed and Two-Tailed Tests

A statistical hypothesis can be one-tailed or two-tailed.

A one-tailed hypothesis involves making a “greater than” or “less than ” statement.

A two-tailed hypothesis involves making an “equal to” or “not equal to” statement.

Note: The “equal” sign is always included in the null hypothesis, whether it is =, ≥, or ≤.

Related: What is a Directional Hypothesis?

## Types of Hypothesis Tests

The following tutorials provide an explanation of the most common types of hypothesis tests:

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## A Beginner’s Guide to Hypothesis Testing in Business

Access your free e-book today.

## What Is Hypothesis Testing?

To understand what hypothesis testing is, it’s important first to understand what a hypothesis is.

## Hypothesis Testing in Business

Related: 9 Fundamental Data Science Skills for Business Professionals

## Key Considerations for Hypothesis Testing

1. alternative hypothesis and null hypothesis.

## IMAGES

## VIDEO

## COMMENTS

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 Frequently asked questions about hypothesis testing Step 1: State your null and alternate hypothesis

Developing a hypothesis (with example) 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 ... Step 2. Do some preliminary research. Step 3. Formulate your hypothesis.

The general idea of hypothesis testing involves: Making an initial assumption. Collecting evidence (data). Based on the available evidence (data), deciding whether to reject or not reject the initial assumption. Every hypothesis test — regardless of the population parameter involved — requires the above three steps. Example S.3.1

To perform hypothesis testing in the first place, you need to collect a sample of data to be analyzed. Depending on the question you’re seeking to answer or investigate, you might collect samples through surveys, observational studies, or experiments.