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| Robustowy test Kruskala-Wallisa× | Test Friedmana× | |
|---|---|---|
| Dziedzina | Statystyka | Statystyka |
| Rodzina | Hypothesis test | Hypothesis test |
| Rok powstania≠ | 1952 (base); robust variants 1990s–2000s | 1937 |
| Twórca≠ | Kruskal & Wallis (1952); robust extensions by Wilcox and others | Milton Friedman |
| Typ≠ | Nonparametric robust rank-based test | Nonparametric repeated-measures comparison (by ranks) |
| Źródło pierwotne≠ | 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. DOI ↗ |
| Inne nazwy≠ | 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 |
| Pokrewne≠ | 3 | 2 |
| Podsumowanie≠ | 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. |
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