Introduction to the linear model. Multiple linear regression. Parameter estimation of the model. Properties of estimators. Hypothesis testing (t and F-tests), coefficient of determination R2, confidence intervals of model coefficients. Residual analysis, diagnostic tests. Prediction. Multicollinearity, heteroskedasticity and other problems. Transformations. Weighted least squares method. Variable selection methods. Influence. Cook s distance. Dummy variables. Analysis of variance and its relation to the linear model. Poisson regression. Logistic regression. Laboratories using statistical software.
- Teacher: Σωτήριος Σαμπάνης
ECTS : 5
Language : el