Porovnat metody

	Analýza kovariance (ANCOVA)	Nezávislý t-test	Jednofaktorová analýza rozptylu
Obor	Statistika	Statistika	Statistika
Rodina	Hypothesis test	Hypothesis test	Hypothesis test
Rok vzniku	1932	1908	1925
Tvůrce	Ronald A. Fisher	Student (W. S. Gosset)	Ronald A. Fisher
Typ	Parametric group comparison with covariate control	Parametric mean comparison	Parametric mean comparison
Původní zdroj	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574	Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25.	Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd.
Další názvy	analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)	student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi	one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA
Příbuzné	4	4	4
Shrnutí	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.	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.