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| ANOVA Mista× | Analisi della Covarianza (ANCOVA)× | |
|---|---|---|
| Campo | Statistica | Statistica |
| Famiglia | Hypothesis test | Hypothesis test |
| Anno di origine≠ | 1925 | 1932 |
| Ideatore≠ | R. A. Fisher (ANOVA framework); split-plot design formalised in agricultural experimentation | Ronald A. Fisher |
| Tipo≠ | Parametric factorial ANOVA | Parametric group comparison with covariate control |
| Fonte seminale≠ | 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 |
| Alias≠ | split-plot ANOVA, mixed-design ANOVA, between-within ANOVA, Karma ANOVA (Mixed ANOVA — Gruplar Arası × Tekrarlı) | analysis of covariance, covariance analysis, ANCOVA (Kovaryans Analizi) |
| Correlati≠ | 6 | 4 |
| Sintesi≠ | 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). |
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