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| Multivariate Varianzanalyse (MANOVA)× | Einfaktorielle Varianzanalyse× | t-Test für abhängige Stichproben× | |
|---|---|---|---|
| Fachgebiet | Statistik | Statistik | Statistik |
| Familie | Hypothesis test | Hypothesis test | Hypothesis test |
| Entstehungsjahr≠ | 1932 | 1925 | 1908 |
| Urheber≠ | Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.) | Ronald A. Fisher | Student (W. S. Gosset) |
| Typ≠ | Parametric multivariate mean comparison | Parametric mean comparison | Parametric mean comparison (paired) |
| Wegweisende Quelle≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Fisher, R. A. (1925). Statistical Methods for Research Workers. Edinburgh: Oliver and Boyd. link ↗ | Field, A. (2013). Discovering Statistics Using IBM SPSS Statistics (4th ed.). SAGE. ISBN: 978-1446249185 |
| Aliasnamen≠ | Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA) | one-factor ANOVA, single-factor ANOVA, analysis of variance, tek yönlü ANOVA | dependent samples t-test, repeated measures t-test, matched-pairs t-test, eşleştirilmiş örneklem t-testi |
| Verwandt≠ | 5 | 4 | 4 |
| Zusammenfassung≠ | MANOVA is a parametric hypothesis test that simultaneously compares group means across multiple continuous dependent variables, controlling the inflation of Type I error that would result from running separate ANOVAs. Key multivariate test statistics — Wilks' Lambda, Pillai's Trace, Hotelling-Lawley Trace, and Roy's Greatest Root — were developed between the 1930s and 1950s, with Wilks' Lambda formalised by Samuel Stanley Wilks in 1932. | One-way ANOVA is a parametric hypothesis test that compares the means of three or more independent groups on a single continuous outcome to decide whether at least one group mean differs. It rests on the variance-partitioning framework introduced by Ronald A. Fisher in 1925. | 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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