Lecturers:
Michela Battauz, Valentina Mameli (University of Udine)

Board Contact:
Valentina Mameli

INTRODUCTION TO R

• Introduction to R
• Explorative data analysis
• Examples of hypothesis test: Student T-test, Two-sample independent T-test, Paired Samples T-test, Chi-square test.

DATA PREPROCESSING

• Missing data
• Principal component analysis
• Cluster analysis: Hierarchical clustering, Partitive clustering (K-Means)

VARIABLE SELECTION

• Classical approaches: best subset selection, forward selection, backward elimination, stepwise regression.
• Modern approaches: shrinkage methods (ridge, lasso), boosting.

MODEL EVALUATION

• Information criteria
• Cross-validation

ANALYSIS OF VARIANCE

All lectures will be supplemented by practical examples carried out using the R software.