Sumários
Lecture 5.
23 Março 2018, 08:30 • Rui Paulo
Saturated model, likehood ratio between satuarted and current and saturated model.
Deviance a and scaled deviance. Assessing the statistical significance of nested models. Table of deviances. Examples.
The normal case: the scaled deviance is the residual sum of squares. Relationship with the ANOVA F-tests.
Lecture 4
16 Março 2018, 08:30 • Rui Paulo
The three ingredients of a generalized linear model. Linear predictor and link function.
Example: binary response. A predictor containing a factor and a numerical variable. Dummy variables and interpretation. Interaction terms.
General consideration regarding main effects and interaction in a linear predictor. Associated number of parameters and notation.
Lecture 3
9 Março 2018, 08:30 • Rui Paulo
The exponential family of distributions. Definition, natural parameter, mean and variance, variance function. Examples: Gaussian, binomial, Poisson and gamma distributions.
Lecture 2
2 Março 2018, 08:30 • Rui Paulo
Multiple linear regression. Matrix formulation of OLS estimates and sums of squares, Properties of estimators. Adjusted R-squared.
The normal linear regression model. Inference: confidence intervals, t- and F-tests.
The normal linear regression model in R.