Comparar métodos
Examine os métodos selecionados lado a lado; as linhas que diferem ficam destacadas.
| Análise de Variância de Welch× | Teste H de Kruskal-Wallis× | |
|---|---|---|
| Área | Estatística | Estatística |
| Família | Hypothesis test | Hypothesis test |
| Ano de origem≠ | 1951 | 1952 |
| Autor original≠ | B. L. Welch | William Kruskal & W. Allen Wallis |
| Tipo≠ | Parametric mean comparison (heteroscedastic) | Nonparametric group comparison |
| Fonte seminal≠ | Welch, B.L. (1951). On the Comparison of Several Mean Values. Biometrika, 38(3/4), 330–336. link ↗ | Kruskal, W. H. & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621. DOI ↗ |
| Outros nomes≠ | Welch's F-test, heteroscedastic one-way ANOVA, Welch ANOVA — Heterojen Varyans ANOVA | Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testi |
| Relacionados≠ | 3 | 5 |
| Resumo≠ | Welch ANOVA is a parametric hypothesis test that compares the means of three or more independent groups when their variances are not equal. Introduced by B. L. Welch in 1951, it replaces classic one-way ANOVA whenever the homogeneity-of-variance assumption fails, while still requiring approximately normal data. | The Kruskal-Wallis H test is a nonparametric hypothesis test that compares three or more independent groups to decide whether their distributions (typically their medians) differ. Introduced by William Kruskal and W. Allen Wallis in 1952, it works on ranks rather than raw values and is the distribution-free counterpart to one-way ANOVA. |
| ScholarGateConjunto de dados ↗ |
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