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| 브루너-문젤 검정(Brunner-Munzel Test)× | Mann-Whitney U 검정× | |
|---|---|---|
| 분야 | 통계학 | 통계학 |
| 계열 | Hypothesis test | Hypothesis test |
| 기원 연도≠ | 2000 | 1947 |
| 창시자≠ | Edgar Brunner & Ullrich Munzel | H. B. Mann & D. R. Whitney |
| 유형≠ | Nonparametric two-sample comparison | Nonparametric two-group comparison |
| 원전≠ | Brunner, E. & Munzel, U. (2000). The Nonparametric Behrens-Fisher Problem: Asymptotic Theory and a Small-Sample Approximation. Biometrical Journal, 42(1), 17–25. DOI ↗ | Mann, H. B. & Whitney, D. R. (1947). On a test of whether one of two random variables is stochastically larger than the other. Annals of Mathematical Statistics, 18(1), 50–60. DOI ↗ |
| 별칭≠ | Brunner-Munzel Testi, generalized Wilcoxon test, nonparametric Behrens-Fisher test, probabilistic index test | Mann-Whitney-Wilcoxon test, Wilcoxon rank-sum test, Mann-Whitney U Testi |
| 관련≠ | 6 | 4 |
| 요약≠ | 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 Mann-Whitney U test is the nonparametric alternative to the independent samples t-test, comparing two independent groups by ranking all observations together rather than relying on their means. It was introduced by H. B. Mann and D. R. Whitney in 1947 and does not require the data to be normally distributed. |
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