The Friedman test is a non-parametric statistical procedure used to analyze variations across three or more matched groups when data follows a dependent samples design and violates the assumption of normality required for repeated measures analysis of variance (ANOVA). This method operates by ranking observations within each block rather than using raw values, thereby testing whether rank sums differ significantly without requiring an underlying distribution. It serves as the non-parametric equivalent to one-way ANOVA with repeated measures within the domain of hypothesis testing and inferential statistics.
Prerequisite chain context: requires Ranks and Rank Sums in Nonparametric Statistics.