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双向方差分析(Two-Way ANOVA)×多元方差分析 (MANOVA)×单因素方差分析×
领域统计学统计学统计学
方法族Hypothesis testHypothesis testHypothesis test
起源年份192519321925
提出者Ronald A. FisherSamuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)Ronald A. Fisher
类型Parametric factorial mean comparisonParametric multivariate mean comparisonParametric mean comparison
开创性文献Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478Tabachnick, 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 ↗
别名factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVAMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
相关654
摘要Two-Way ANOVA is a parametric hypothesis test that simultaneously examines the main effects of two independent categorical factors and their interaction effect on a single continuous dependent variable. The technique was developed within the broader framework of the analysis of variance established by Ronald A. Fisher in 1925 and remains the standard approach whenever an experiment or survey includes exactly two between-subjects factors.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.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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ScholarGate方法对比: Two-Way ANOVA · MANOVA · One-way ANOVA. 于 2026-06-20 检索自 https://scholargate.app/zh/compare