The normality assumption is a statistical premise that assumes data follows a normal distribution, which is crucial for the validity of many parametric tests such as t-tests and ANOVA. Deviations from normality can lead to incorrect conclusions, making it essential to assess and, if necessary, transform data to meet this assumption.