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There are two possible hypotheses in a paired t-test.

What are the hypotheses of a paired t-test? Paired t-tests are considered more powerful than unpaired t-tests because using the same participants or item eliminates variation between the samples that could be caused by anything other than what’s being tested.

The groups can be related by being the same group of people, the same item, or being subjected to the same conditions.

A significant difference occurs when the differences between groups are unlikely to be due to sampling error or chance.

What is a paired t-test?Ī paired t-test (also known as a dependent or correlated t-test) is a statistical test that compares the averages/means and standard deviations of two related groups to determine if there is a significant difference between the two groups. This article will explain when it is appropriate to use a paired t-test versus an unpaired t-test, as well as the hypothesis and assumptions of each.

These statistical tests are commonly used in research in the fields of biology, business, and psychology. Student’s t-tests are further broken down into two categories: paired t-tests and unpaired t-tests. Also known as Student’s t-tests, their results are used to determine if there is a significant difference between the mean of two samples that is unlikely to be due to sampling error or random chance. Two-sample t-tests are statistical tests used to compare the means of two populations.