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Bekijk de geselecteerde methoden naast elkaar; rijen die verschillen zijn gemarkeerd.

Onafhankelijke t-toets voor twee steekproeven×Multivariate Analysis of Variance (MANOVA)×Multivariate Meervoudige Lineaire Regressie×
VakgebiedStatistiekStatistiekStatistiek
FamilieHypothesis testHypothesis testRegression model
Jaar van ontstaan190819322007
GrondleggerStudent (W. S. Gosset)Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)Johnson & Wichern (textbook treatment); classical multivariate least squares
TypeParametric mean comparisonParametric multivariate mean comparisonMultivariate linear regression
Oorspronkelijke bronStudent (1908). The probable error of a mean. Biometrika, 6(1), 1–25. DOI ↗Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574Johnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153
Aliassenstudent t-test, two-sample t-test, unpaired t-test, bağımsız örneklem t-testiMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)multivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV)
Verwant455
SamenvattingThe 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.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.Multivariate regression is a linear regression method that predicts several continuous dependent variables at the same time from a shared set of predictors. As developed in standard treatments such as Johnson and Wichern's Applied Multivariate Statistical Analysis (2007), each response equation can be fitted by ordinary least squares while the covariance structure of the residuals is used for joint testing across outcomes.
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ScholarGateMethoden vergelijken: Independent t-test · MANOVA · Multivariate Regression. Geraadpleegd op 2026-06-20 via https://scholargate.app/nl/compare