Σύγκριση μεθόδων

	Ανάμεικτη Ανάλυση Διακύμανσης (Mixed ANOVA)	Ανάλυση Συνδιακύμανσης (ANCOVA)	t-test for paired samples
Πεδίο	Στατιστική	Στατιστική	Στατιστική
Οικογένεια	Hypothesis test	Hypothesis test	Hypothesis test
Έτος προέλευσης	1925	1932	1908
Δημιουργός	R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation	Ronald A. Fisher	Student (W. S. Gosset)
Τύπος	Parametric factorial ANOVA	Parametric group comparison with covariate control	Parametric mean comparison (paired)
Θεμελιώδης πηγή	Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE. ISBN: 978-1526419521	Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574	Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185
Εναλλακτικές ονομασίες	split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı)	analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi)	dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş örneklem t-testi
Συναφείς	6	4	4
Σύνοψη	Mixed ANOVA is a parametric factorial analysis of variance that simultaneously examines at least one between-subjects factor and at least one within-subjects (repeated-measures) factor. Rooted in R. A. Fisher's ANOVA framework formalised in 1925, it is the standard method for experimental and longitudinal designs in which different groups are each measured across multiple time points or conditions.	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 paired samples t-test is a parametric hypothesis test that compares two measurements taken on the same subjects — such as a before and after reading — to decide whether the average change differs from zero. It rests on the t-distribution introduced by Student (W. S. Gosset) in 1908 and works on the within-subject difference scores rather than the raw measurements.