STA230 — Statistical Learning
Welcome to the interactive learning companion for STA230 Statistical Learning at the University of Gothenburg.
This site covers all three course blocks — with concept explanations, multiple-choice quizzes, and interactive R code you can run and modify directly in the browser.
1 Course structure
| Block | Topics |
|---|---|
| Foundations | What is statistical learning? Bias-variance tradeoff, training vs test error, cross-validation |
| Block 1: Regression | OLS, variable selection, ridge regression, LASSO |
| Block 2: Classification | Logistic regression, LDA/kNN, decision trees, random forests, boosting, ROC/AUC, calibration |
| Block 3: Unsupervised | PCA, k-means clustering, hierarchical clustering, PAM, t-SNE, UMAP |
2 How to use this site
- Read the concept section — short and focused
- Answer the quiz — tests comprehension before you see code
- Run and modify the code — the key learning step
- Use the Guided Practice exercises with real datasets
- Click Mark as complete when done — your progress is saved in the browser
TipCoding is the way to learn
The central principle of STA230: understanding comes from doing, not reading. Every section ends with hands-on exercises using real datasets (Hitters, NHANES, SWP_CTW).