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多変量分散分析 (MANOVA)×共分散分析(ANCOVA)×独立標本t検定×
分野統計学統計学統計学
系統Hypothesis testHypothesis testHypothesis test
提唱年193219321908
提唱者Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)Ronald A. FisherStudent (W. S. Gosset)
種類Parametric multivariate mean comparisonParametric group comparison with covariate controlParametric mean comparison
原典Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗
別名Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi
関連544
概要MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932.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).The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances.
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ScholarGate手法を比較: MANOVA · ANCOVA · Independent t-test. 2026-06-20に以下より取得 https://scholargate.app/ja/compare