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Dunn의 다중 비교 검정×프리드만 검정×Nemenyi 사후 검정 (Friedman 검정)×
분야통계학통계학통계학
계열Hypothesis testHypothesis testHypothesis test
기원 연도196419371963
창시자Olive Jean DunnMilton FriedmanPeter Nemenyi
유형Nonparametric pairwise comparisonNonparametric repeated-measures comparison (by ranks)Nonparametric post-hoc multiple comparison
원전Dunn, O.J. (1964). Multiple Comparisons Using Rank Sums. Technometrics, 6(3), 241–252. DOI ↗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 ↗Nemenyi, P. (1963). Distribution-Free Multiple Comparisons. PhD thesis, Princeton University. link ↗
별칭Dunn's post-hoc test, Kruskal-Wallis post-hoc, Dunn Testi — Kruskal-Wallis Post-HocFriedman two-way analysis of variance by ranks, Friedman rank test, Friedman TestiNemenyi Testi — Friedman Post-Hoc, Nemenyi multiple comparison test, Nemenyi procedure
관련525
요약Dunn's test is a nonparametric post-hoc procedure introduced by Olive Jean Dunn in 1964 to identify which specific pairs of groups differ significantly after a Kruskal-Wallis test has returned a significant overall result. It compares groups pairwise using rank sums and applies a multiple-comparison correction — most commonly Bonferroni or Holm — to control the family-wise error rate.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.The Nemenyi test is a nonparametric post-hoc multiple comparison procedure introduced by Peter Nemenyi in his 1963 Princeton doctoral thesis. It is applied after a significant Friedman test to identify which specific pairs of conditions differ from each other in a repeated-measures or blocked design.
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ScholarGate방법 비교: Dunn Test · Friedman test · Nemenyi Test. 2026-06-19에 다음에서 검색함: https://scholargate.app/ko/compare