Behavioral Research: Statistical Methods

When the data **refuse to behave** — ordinal scale, heavily skewed, unfixable outliers, tiny n — drop the Normality assumption and use **non-parametric tests**. Each non-parametric test pairs to a parametric cousin: independent t ↔ Mann-Whitney; paired t ↔ Wilcoxon signed-rank; one-way ANOVA ↔ Kruskal-Wallis; repeated-measures ANOVA ↔ Friedman; Pearson r ↔ Spearman ρ. **χ²** handles purely categorical data; **McNemar** handles paired proportions; **Fisher's exact** handles small counts. Non-parametric tests have **less power than parametric when parametric assumptions actually hold** — use them only when needed.