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सहप्रसरण विश्लेषण (ANCOVA)×क्रुस्कल-वालिस H परीक्षण×एक-तरफ़ा विचरण विश्लेषण×
क्षेत्रसांख्यिकीसांख्यिकीसांख्यिकी
परिवारHypothesis testHypothesis testHypothesis test
उद्भव वर्ष193219521925
प्रवर्तकRonald A. FisherWilliam Kruskal & W. Allen WallisRonald A. Fisher
प्रकारParametric group comparison with covariate controlNonparametric group comparisonParametric mean comparison
मौलिक स्रोतTabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Kruskal, 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 ↗Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗
उपनामanalysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)Kruskal-Wallis H test, one-way ANOVA on ranks, Kruskal-Wallis one-way analysis of variance, Kruskal-Wallis Testione-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
संबंधित454
सारांशANCOVA is a parametric hypothesis test that compares the adjusted means of two or more independent groups while statistically controlling for one or more continuous covariates. By removing the portion of outcome variance explained by the covariate, ANCOVA increases statistical precision and produces fairer group comparisons. The method builds on the general linear model framework consolidated by Fisher in the early 1930s and is described comprehensively by Tabachnick and Fidell (2013).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.One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925.
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