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वेल्च का विचरण विश्लेषण (Welch's Analysis of Variance)×क्रुस्कल-वालिस H परीक्षण×वेल्च की टी-परीक्षा (असमान प्रसरण)×
क्षेत्रसांख्यिकीसांख्यिकीसांख्यिकी
परिवारHypothesis testHypothesis testHypothesis test
उद्भव वर्ष195119521947
प्रवर्तकB. L. WelchWilliam Kruskal & W. Allen WallisB. L. Welch
प्रकारParametric mean comparison (heteroscedastic)Nonparametric group comparisonParametric mean comparison (unequal variances)
मौलिक स्रोतWelch, 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 ↗Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35. DOI ↗
उपनामWelch's F-test, heteroscedastic one-way ANOVA, Welch ANOVA — Heterojen Varyans ANOVAKruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testiunequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans)
संबंधित354
सारांशWelch 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.Welch's t-test is a parametric hypothesis test that compares the means of two independent groups without assuming their variances are equal. It was introduced by B. L. Welch in 1947 as a more robust generalization of Student's two-sample test for situations where the two groups have different spread.
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