Lecture 2

6 Março 2020, 08:00 • RUI MIGUEL BATISTA PAULO

Multiple linear regression. Least squares estimate in matrix formulation. Properties of the OLS estimator. Adjusted R-squared.

Normal multiple regression model. Inference on the regression coefficients.

Example using R. Interpretation of the coefficients and individual significance.

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Lecture 1

28 Fevereiro 2020, 08:00 • RUI MIGUEL BATISTA PAULO

Review of linear regression. Matrix formulation of multiple linear regression. Simple linear regression. Hypotheses of the model, least square estimates and properties. Residuals and fitted values. Decomposition of the total variance. Coefficient of determination. Simple linear regression in R.

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Lecture 0

21 Fevereiro 2020, 08:00 • RUI MIGUEL BATISTA PAULO

Assessment, bibliography and general goals of the unit.

Brief description of generalized linear models.

A tour of the R environment for statistical computing. 

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