Σύγκριση μεθόδων

	Ανάμεικτη Ανάλυση Διακύμανσης (Mixed ANOVA)	t-test for paired samples
Πεδίο	Στατιστική	Στατιστική
Οικογένεια	Hypothesis test	Hypothesis test
Έτος προέλευσης	1925	1908
Δημιουργός	R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation	Student (W. S. Gosset)
Τύπος	Parametric factorial ANOVA	Parametric mean comparison (paired)
Θεμελιώδης πηγή	Field, A. (2018). Discovering Statistics Using IBM SPSS Statistics (5th ed.). SAGE. ISBN: 978-1526419521	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)	dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş örneklem t-testi
Συναφείς	6	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.	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.