Normality Test

Test whether your data follows a normal distribution using Shapiro-Wilk, Kolmogorov-Smirnov, and Anderson-Darling tests, with Q-Q plots and histograms.

With large samples, normality tests become highly sensitive and will often reject normality due to trivial deviations that have no practical significance. Always interpret results alongside the Q-Q plot, histogram, and effect size, a statistically significant p-value alone is not sufficient evidence of meaningful non-normality.