Порівняння методів

	Двофакторний дисперсійний аналіз (Two-Way ANOVA)	Дисперсійний аналіз з коваріатою (ANCOVA)	Крускала-Волліса H-критерій	Багатовимірний дисперсійний аналіз (MANOVA)
Галузь	Статистика	Статистика	Статистика	Статистика
Родина	Hypothesis test	Hypothesis test	Hypothesis test	Hypothesis test
Рік появи	1925	1932	1952	1932
Автор методу	Ronald A. Fisher	Ronald A. Fisher	William Kruskal & W. Allen Wallis	Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)
Тип	Parametric factorial mean comparison	Parametric group comparison with covariate control	Nonparametric group comparison	Parametric multivariate mean comparison
Основоположне джерело	Montgomery, D. C. (2017). Design and Analysis of Experiments (9th ed.). Wiley. ISBN: 978-1119113478	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574	Kruskal, W. H. & Wallis, W. A. (1952). Use of ranks in one-criterion variance analysis. Journal of the American Statistical Association, 47(260), 583–621.	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
Інші назви	factorial ANOVA, two-factor ANOVA, İki Yönlü ANOVA	analysis 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 Testi	Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)
Пов'язані	6	4	5	5
Підсумок	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.	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 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.	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.