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اختبار T² لهوتيلينج×تحليل التغاير المتعدد المتغيرات (MANCOVA)×تحليل التباين متعدد المتغيرات (MANOVA)×
المجالالإحصاءالإحصاءالإحصاء
العائلةHypothesis testHypothesis testHypothesis test
سنة النشأة193119701932
صاحب الطريقةHarold HotellingExtension of MANOVA and ANCOVA traditions; consolidated in multivariate textbooks by the 1970s–1980sSamuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.)
النوعMultivariate parametric mean comparisonParametric multivariate mean comparison with covariate controlParametric multivariate mean comparison
المصدر التأسيسيHotelling, H. (1931). The Generalization of Student's Ratio. Annals of Mathematical Statistics, 2(3), 360–378. link ↗Tabachnick, B. G. & Fidell, L. S. (2019). Using Multivariate Statistics (7th ed.). Pearson. ISBN: 978-0134790541Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574
الأسماء البديلةHotelling T² Testi — Çok Değişkenli t-Testi, multivariate t-test, Hotelling T-squaredMANCOVA, multivariate ANCOVA, MANOVA with covariates, MANCOVA — Çok Değişkenli Kovaryans AnaliziMultivariate ANOVA, Çok Değişkenli ANOVA (MANOVA)
ذات صلة655
الملخصHotelling's T² test is a multivariate parametric hypothesis test that simultaneously compares the mean vectors of two independent groups across multiple continuous outcome variables. It was introduced by Harold Hotelling in 1931 as the direct multivariate generalization of Student's t-test, replacing the scalar mean difference with a vector difference scaled by the pooled variance-covariance matrix.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).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.
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ScholarGateقارن الطرق: Hotelling's T² Test · MANCOVA · MANOVA. استُرجع بتاريخ 2026-06-20 من https://scholargate.app/ar/compare