The paired-samples t test is appropriate whenever two related sample means are to be compared. The difference scores are assumed to follow a reasonably normal distribution, especially with respect to skewness. Before running the t test, you can assess the distribution of difference scores by examining the histogram of a computed difference variable. Test variables with extreme or outlying values should be carefully checked; boxplots can be used for this.

- Use the Explore procedure or the One-Sample Kolmogorov-Smirnov Test procedure to test the assumption of normality.
- Use the Runs Test procedure to check the assumption that the value of the test variable is independent of the order of observation.
- If you compute the difference between the paired variables, you can alternatively use the One-Sample T Test procedure.
- If your test variables do not satisfy the assumptions of the paired t test, try the Wilcoxon signed-rank test in the Two-Related-Samples Tests procedure.