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- Independent-Samples t-Test
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- Chi-Squared (χ2) Test of Association
- Shapiro-Wilk Test of Normality
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We have provided some guides to help you with carrying out many commonly used statistical tests.

This list of statistical tests is not exhaustive.

We show you the process of carrying out the test in SPSS, examples of the output that it will produce, and an example of how you could report it using the correct APA style.

If there is a test or statistical method you would like to see here, please email us your suggestion.

*between-subjects design*. If we have one participant group and we measure them multiple times, we can test if there is a difference in the repeated measurement and therefore, we have a *repeated-measures design*.

In some subjects, like Psychology, a *repeated-measures design is called a within-subjects design.*

Data may be described as as **parametric**, for data to be parametric it must possess four characterises sometimes called the Parametric Assumptions. Data is parametric if it is normally distributed, homogenous, interval level (or higher) and independent.

Parametric tests, such as an Independent Samples t-Test, should only be used on parametric data, if your data is non-parametric you should use a non-parametric alternative, such as the Mann-Whitney U-Test

For more information on determining if your data is parametric or not, please our guide:

You can also directly test if the data is normally distributed by conducting a normality test, such as a Shapiro-Wilk test. Other normality tests can be used, choices of which are often determined by research field and sample size.

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