This guide contains all of the ASC's statistics resources. If you do not see a topic, suggest it through the suggestion box on the Statistics home page.

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**Two-tailed Test**

When testing a hypothesis, you must determine if it is a one-tailed or a two-tailed test. The most common format is a two-tailed test, meaning the critical region is located in both tails of the distribution. This is also referred to as a *non-directional* hypothesis.

This type of test is associated with a "neutral" alternative hypothesis. Here are some examples:

- There
*is a difference*between the scores. - The groups are
*not equal*. - There
*is a relationship*between the variables.

**One-tailed Test**

The alternative option is a one-tailed test. As the name implies, the critical region lies in only one tail of the distribution. This is also called a *directional* hypothesis. The image below shows a right-tailed test. A left-tailed test would be another type of one-tailed test.

This type of test is associated with a more specific alternative claim. Here are some examples:

- One group is
*higher*than the other. - There is a
*decrease*in performance. - Group A performs
*worse than*Group B.

- Last Updated: Oct 3, 2024 5:13 PM
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