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Robust Kruskal-Wallis-test×Friedman-testen×
FagfeltStatistikkStatistikk
FamilieHypothesis testHypothesis test
Opprinnelsesår1952 (base); robust variants 1990s–2000s1937
OpphavspersonKruskal & Wallis (1952); robust extensions by Wilcox and othersMilton Friedman
TypeNonparametric robust rank-based testNonparametric repeated-measures comparison (by ranks)
Opprinnelig kildeMielke, P. W., & Berry, K. J. (2007). Permutation Methods: A Distance Function Approach (2nd ed.). Springer. ISBN: 978-0387698137Friedman, 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. DOI ↗
Aliasrobust K-W test, trimmed Kruskal-Wallis, robust nonparametric one-way test, robust rank-based ANOVAFriedman two-way analysis of variance by ranks, Friedman rank test, Friedman Testi
Relaterte32
SammendragThe 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.
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ScholarGateSammenlign metoder: Robust Kruskal-Wallis test · Friedman test. Hentet 2026-06-18 fra https://scholargate.app/no/compare