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| Unabhängiger t-Test für zwei Stichproben× | Multivariate Analysis of Covariance (MANCOVA)× | |
|---|---|---|
| Fachgebiet | Statistik | Statistik |
| Familie | Hypothesis test | Hypothesis test |
| Entstehungsjahr≠ | 1908 | 1970 |
| Urheber≠ | Student (W. S. Gosset) | Extension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980s |
| Typ≠ | Parametric mean comparison | Parametric multivariate mean comparison with covariate control |
| Wegweisende Quelle≠ | Student (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗ | Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541 |
| Aliasnamen | student t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testi | MANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans Analizi |
| Verwandt≠ | 4 | 5 |
| Zusammenfassung≠ | The independent samples t-test is a parametric hypothesis test that compares the means of two independent groups to decide whether they differ significantly. It builds on the t-distribution introduced by Student (W. S. Gosset) in 1908 and assumes the measured values are continuous, approximately normally distributed, and have equal variances. | MANCOVA (Multivariate Analysis of Covariance) is a parametric hypothesis test that simultaneously compares two or more groups on multiple continuous dependent variables while statistically controlling for one or more covariates. It extends MANOVA by incorporating covariate adjustment, a tradition consolidated in multivariate statistical methodology by the 1970s and authoritatively documented by Tabachnick and Fidell (2019). |
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