विधियों की तुलना करें
चुनी हुई विधियों की आमने-सामने समीक्षा करें; भिन्नता वाली पंक्तियाँ रेखांकित हैं।
| बहुभिन्नरूपी प्रसरण विश्लेषण (MANOVA)× | बहुचर एकाधिक रैखिक समाश्रयण× | |
|---|---|---|
| क्षेत्र | सांख्यिकी | सांख्यिकी |
| परिवार≠ | Hypothesis test | Regression model |
| उद्भव वर्ष≠ | 1932 | 2007 |
| प्रवर्तक≠ | Samuel Stanley Wilks (Wilks' Lambda, 1932); Roy, Hotelling, Pillai (mid-20th c.) | Johnson & Wichern (textbook treatment); classical multivariate least squares |
| प्रकार≠ | Parametric multivariate mean comparison | Multivariate linear regression |
| मौलिक स्रोत≠ | Tabachnick, B.G. & Fidell, L.S. (2013). Using Multivariate Statistics (6th ed.). Pearson. ISBN: 978-0205849574 | Johnson, R. A. & Wichern, D. W. (2007). Applied Multivariate Statistical Analysis (6th ed.). Pearson. ISBN: 978-0131877153 |
| उपनाम≠ | Multivariate ANOVA, Çok Değişkenli ANOVA (MANOVA) | multivariate multiple regression, MLR with multiple dependent variables, multiple-outcome regression, Çok Değişkenli Regresyon (MLR — Çoklu DV) |
| संबंधित | 5 | 5 |
| सारांश≠ | 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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