Many statistical tests that are commonly used rely on the assumption that data are normally distributed. This chapter discusses why normality commonly occurs in statistics but also how, in many practical situations in HCI, it is not safe to assume normality. It also shows how tests for normality are not meaningful or useful. Instead, where normality is in doubt, analysis should be more careful and use suitable alternative tests.