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Analiza kowariancji (ANCOVA)×Jednoczynnikowa analiza wariancji×Test t Welcha (nierówne wariancje)×
DziedzinaStatystykaStatystykaStatystyka
RodzinaHypothesis testHypothesis testHypothesis test
Rok powstania193219251947
TwórcaRonald A. FisherRonald A. FisherB. L. Welch
TypParametric group comparison with covariate controlParametric mean comparisonParametric mean comparison (unequal variances)
Źródło pierwotneTabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗Welch, B. L. (1947). The generalization of Student's problem when several different population variances are involved. Biometrika, 34(1/2), 28–35. DOI ↗
Inne nazwyanalysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVAunequal variances t-test, Welch-Satterthwaite t-test, Welch t-Testi (Eşit Olmayan Varyans)
Pokrewne444
PodsumowanieANCOVA 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).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.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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ScholarGatePorównaj metody: ANCOVA · One-way ANOVA · Welch t-test. Pobrano 2026-06-20 z https://scholargate.app/pl/compare