Introduction to statistical data analysis

A. Laio and M.S. Bernardi, 18 hours

  • Introduction to Statistical Learning

  • Dimension reduction: Principal Components Analysis

  • Linear Models: Simple and multiple linear regression

  • Linear Model Selection and Regularization: Best Subset Selection, Stepwise Selection, Shrinkage Methods (Ridge Regression and Lasso)

  • Supervised classification: Logistic Regression, Linear and Quadratic Discriminant Analysis

  • Unsupervised classification: Hierarchical clustering and K-means clustering

  • Resampling Methods: Cross-Validation and Bootstrap

  • Tree-based Methods: Classification and Regression trees