Multiple linear regression I
Recording date: Jan 13, 2020
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Covariance and correlation. Simple correlation, partial correlation, multiple correlation. The multiple linear regression model. Interpretation of the model. Estimation of the model and hypothesis testing. Explained and residual variance. ANOVA table. Multiple R squared. Adjusted R squared. Residuals and residual analysis. Variable selection: extra sum of squares. Log-linear regression. Polynomial regression. Model with interaction. Prediction.
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: Jacobo de UñaProfessor, University of Vigo
