The one-sample t test can be used whenever sample means must be compared to a known test value. As with all t tests, the one-sample t test assumes that the data be reasonably normally distributed, especially with respect to skewness. Extreme or outlying values should be carefully checked; boxplots are very handy 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.