# Testing assumptions of the t-test

Many statistical tests have assumptions that must be true for the test results to be valid. A pooled sample t-test assumes that the samples are normally distributed and the variances of the groups are equal. It can be useful to verify the assumptions.

Note: Although this tutorial formally tests the assumptions of the t test, many
statisticians would recommend against doing so because the t-test is fairly robust
to departures from normality for moderate sample sizes. Also some homogeneity of
variance tests can be extremely sensitive to departures of normality and may cause
you to believe the variances are not equal.

The p-value of the normality test is not significant so do not reject the null hypothesis. The data can be treated as normally distributed.

The p-value of the homogeneity of variance test is 0.04 so reject the null hypothesis of homogeneity of variances in favor of the alternative hypothesis of a difference in variances.

**Next topic:**Trying a different statistical test

- Tutorials
- Distribution tutorial
- Correlation / PCA tutorial
- Compare groups means tutorial
- Testing for a difference of means
- Testing assumptions of the t-test
- Trying a different statistical test
- Association in 2-way contingency tables tutorial
- Simple linear regression tutorial
- Bland-Altman method comparison tutorial
- Pareto charts tutorial
- Process control charts tutorial
- Process capability tutorial

Published 8-Jan-2017

Version 4.90