Friedman’s ANOVA is the non-parametric counterpart to which parametric test?

Friedman’s ANOVA is the non-parametric counterpart to which parametric test?

• A. Friedman’s ANOVA
• B. One-way ANOVA
• C. Repeated-measures ANOVA
• D. MANOVA

Answer: (A)

Friedman’s test is used when you have related samples (the same subjects measured under several conditions) and you don’t want to assume normality. It serves as the nonparametric counterpart to the repeated-measures ANOVA, which is the parametric test used for comparing means across more than two related conditions. Instead of comparing means, Friedman ranks the data within each subject across the conditions, then analyzes whether the sum of ranks differs across conditions. This mirrors the logic of repeated-measures ANOVA but with ranks, making it suitable for ordinal data or when normality or sphericity assumptions are violated. In contrast, one-way ANOVA is for independent groups, MANOVA handles multiple dependent variables, and the direct counterpart to those scenarios isn’t Friedman. So the appropriate relationship is Friedman’s test to the repeated-measures ANOVA.

Friedman’s test is used when you have related samples (the same subjects measured under several conditions) and you don’t want to assume normality. It serves as the nonparametric counterpart to the repeated-measures ANOVA, which is the parametric test used for comparing means across more than two related conditions. Instead of comparing means, Friedman ranks the data within each subject across the conditions, then analyzes whether the sum of ranks differs across conditions. This mirrors the logic of repeated-measures ANOVA but with ranks, making it suitable for ordinal data or when normality or sphericity assumptions are violated. In contrast, one-way ANOVA is for independent groups, MANOVA handles multiple dependent variables, and the direct counterpart to those scenarios isn’t Friedman. So the appropriate relationship is Friedman’s test to the repeated-measures ANOVA.