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协方差分析 (ANCOVA)×单因素方差分析×Welch's t检验(方差不齐)×
领域统计学统计学统计学
方法族Hypothesis testHypothesis testHypothesis test
起源年份193219251947
提出者Ronald A. FisherRonald A. FisherB. L. Welch
类型Parametric group comparison with covariate controlParametric mean comparisonParametric mean comparison (unequal variances)
开创性文献Tabachnick, 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 ↗
别名analysis 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)
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摘要ANCOVA 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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ScholarGate方法对比: ANCOVA · One-way ANOVA · Welch t-test. 于 2026-06-20 检索自 https://scholargate.app/zh/compare