Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| ANOVA Mixtă× | Analiza de Covarianță (ANCOVA)× | Testul t pentru eșantioane pereche× | |
|---|---|---|---|
| Domeniu | Statistică | Statistică | Statistică |
| Familie | Hypothesis test | Hypothesis test | Hypothesis test |
| Anul apariției≠ | 1925 | 1932 | 1908 |
| Autorul original≠ | R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation | Ronald A. Fisher | Student (W. S. Gosset) |
| Tip≠ | Parametric factorial ANOVA | Parametric group comparison with covariate control | Parametric mean comparison (paired) |
| Sursa seminală≠ | 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 |
| Denumiri alternative≠ | 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 |
| Înrudite≠ | 6 | 4 | 4 |
| Rezumat≠ | 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. |
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