Compara mètodes

	Anàlisi de la Covariància (ANCOVA)	Anàlisi Multivariant de la Covariància (MANCOVA)	Anàlisi de la variància d'un factor
Camp	Estadística	Estadística	Estadística
Família	Hypothesis test	Hypothesis test	Hypothesis test
Any d'origen	1932	1970	1925
Autor original	Ronald A. Fisher	Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s	Ronald A. Fisher
Tipus	Parametric group comparison with covariate control	Parametric multivariate mean comparison with covariate control	Parametric mean comparison
Font seminal	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574	Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Àlies	analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)	MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Relacionats	4	5	4
Resum	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).	MANCOVA (Multivariate Analysis of Covariance) is a parametric hypothesis test that simultaneously compares two or more groups on multiple continuous dependent variables while statistically controlling for one or more covariates. It extends MANOVA by incorporating covariate adjustment, a tradition consolidated in multivariate statistical methodology by the 1970s and authoritatively documented by Tabachnick and Fidell (2019).	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.