Multivariate Linear Regression
Multivariate Linear Regression
Nathaniel E. Helwig Assistant Professor of Psychology and Statistics
University of Minnesota (Twin Cities)
Updated 16-Jan-2017
Nathaniel E. Helwig (U of Minnesota)
Multivariate Linear Regression
Updated 16-Jan-2017 : Slide 1
Copyright
Copyright c 2017 by Nathaniel E. Helwig
Nathaniel E. Helwig (U of Minnesota)
Multivariate Linear Regression
Updated 16-Jan-2017 : Slide 2
Outline of Notes
1) Multiple Linear Regression Model form and assumptions Parameter estimation Inference and prediction
2) Multivariate Linear Regression Model form and assumptions Parameter estimation Inference and prediction
Nathaniel E. Helwig (U of Minnesota)
Multivariate Linear Regression
Updated 16-Jan-2017 : Slide 3
Multiple Linear Regression
Multiple Linear Regression
Nathaniel E. Helwig (U of Minnesota)
Multivariate Linear Regression
Updated 16-Jan-2017 : Slide 4
Multiple Linear Regression Model Form and Assumptions
MLR Model: Scalar Form
The multiple linear regression model has the form
p
yi = b0 + bj xij + ei
j =1
for i {1, . . . , n} where yi R is the real-valued response for the i-th observation b0 R is the regression intercept bj R is the j-th predictor's regression slope xij R is the j-th predictor for the i-th observation ei iid N(0, 2) is a Gaussian error term
Nathaniel E. Helwig (U of Minnesota)
Multivariate Linear Regression
Updated 16-Jan-2017 : Slide 5
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