Comparer des méthodes

	Test de Brunner-Munzel	Test de Fligner-Killeen pour l'homogénéité des variances
Domaine	Statistique	Statistique
Famille	Hypothesis test	Regression model
Année d'origine	2000	1976
Auteur d'origine	Edgar Brunner & Ullrich Munzel	Michael A. Fligner & Timothy J. Killeen
Type	Nonparametric two-sample comparison	Rank-based test for homogeneity of variances
Source fondatrice	Brunner, E. & Munzel, U. (2000). The Nonparametric Behrens-Fisher Problem: Asymptotic Theory and a Small-Sample Approximation. Biometrical Journal, 42(1), 17–25.	Fligner, M. A., & Killeen, T. J. (1976). Distribution-Free Two-Sample Tests for Scale. Journal of the American Statistical Association, 71(353), 210-213.
Alias	Brunner-Munzel Testi, generalized Wilcoxon test, nonparametric Behrens-Fisher test, probabilistic index test	Fligner-Killeen test of variance homogeneity, rank-based variance homogeneity test, Fligner-Killeen Varyans Homojenliği Testi
Apparentées	6	5
Résumé	The Brunner-Munzel test is a nonparametric two-sample hypothesis test that estimates the probabilistic superiority index P(X < Y) — the probability that a randomly selected observation from one group exceeds a randomly selected observation from the other. Introduced by Brunner and Munzel in 2000 as a solution to the nonparametric Behrens-Fisher problem, it remains valid even when the two groups have unequal variances or differently shaped distributions, making it a robust alternative to the Mann-Whitney U test in heteroscedastic settings.	The Fligner-Killeen test is a rank-based test that checks whether several independent groups share the same variance (scale). Introduced by Fligner and Killeen in 1976, it does not require the data to be normally distributed, making it a robust nonparametric alternative to the Levene and Bartlett tests.