Porovnat metody

	Robustní Kruskal-Wallisův test	Friedmanův test
Obor	Statistika	Statistika
Rodina	Hypothesis test	Hypothesis test
Rok vzniku	1952 (base); robust variants 1990s–2000s	1937
Tvůrce	Kruskal & Wallis (1952); robust extensions by Wilcox and others	Milton Friedman
Typ	Nonparametric robust rank-based test	Nonparametric repeated-measures comparison (by ranks)
Původní zdroj	Mielke, P. W., & Berry, K. J. (2007). Permutation Methods: A Distance Function Approach (2nd ed.). Springer. ISBN: 978-0387698137	Friedman, M. (1937). The use of ranks to avoid the assumption of normality implicit in the analysis of variance. Journal of the American Statistical Association, 32(200), 675–701.
Další názvy	robust K-W test, trimmed Kruskal-Wallis, robust nonparametric one-way test, robust rank-based ANOVA	Friedman two-way analysis of variance by ranks, Friedman rank test, Friedman Testi
Příbuzné	3	2
Shrnutí	The robust Kruskal-Wallis test is a nonparametric, rank-based method for comparing three or more independent groups when data contain outliers, heavy tails, or heterogeneous spread. It augments the classical Kruskal-Wallis H statistic with robust techniques — such as trimmed means on ranks or permutation-based inference — to maintain valid Type I error rates even when distributional assumptions are violated.	The Friedman test is a nonparametric hypothesis test that compares three or more related conditions measured on the same blocks or subjects, serving as the rank-based alternative to repeated-measures ANOVA. It was introduced by Milton Friedman in 1937 and works on ordinal or continuous data without assuming normality.