Compară metode
Examinează metodele selectate una lângă alta; rândurile care diferă sunt evidențiate.
| Analiza de Covarianță (ANCOVA)× | Testul t pentru eșantioane pereche× | |
|---|---|---|
| Domeniu | Statistică | Statistică |
| Familie | Hypothesis test | Hypothesis test |
| Anul apariției≠ | 1932 | 1908 |
| Autorul original≠ | Ronald A. Fisher | Student (W. S. Gosset) |
| Tip≠ | Parametric group comparison with covariate control | Parametric mean comparison (paired) |
| Sursa seminală≠ | 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≠ | 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 | 4 | 4 |
| Rezumat≠ | 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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