Robust against non-normality

This fact sheet provides applied guidance on robustness to non-normality in common parametric analyses, including t-tests, ANOVA, and regression. It explains how sample size, residual behaviour, skewness, kurtosis, and variance heterogeneity influence statistical inference, and clarifies when violations of normality are practically consequential. The document emphasises graphical diagnostics over formal tests and offers evidence-based recommendations for researchers analysing real-world data.