| Lecture | Slides | R script |
|---|---|---|
| Lecture 1: Introduction to predictive analytics | Slides | |
| Lecture 2: Probability 1 | Slides | Script |
| Lecture 3: Probability 2 | Slides | Script |
| Lecture 4: Bayes' Rule & Random Variables | Slides | Script |
| Lecture 5: Making Decisions | Slides | Script |
| Lecture 6: Decision Trees | Slides | |
| Lecture 7: Value of Information | Slides | |
| Lecture 8: Review of Inference | Slides | Script |
| Lecture 9: Correlation & Simple Regression 1 | Slides | Script |
| Lecture 10: Correlation & Simple Regression 2 | Slides | Script |
| Lecture 11: Inference for Simple Regression 1 | Slides | Script |
| Lecture 12: Inference for Simple Regression 2 | Slides | Script |
| Lecture 13: What can go wrong, and how to fix it 1 | Slides | Script |
| Lecture 14: What can go wrong, and how to fix it 2 | Slides | Script |
| Lecture 15: Multiple Regression | Slides | Script |
| Lecture 16: Polynomial Regression & Data Cleaning | Slides | Script |
| Lecture 17: Building Models | Slides | Script |
| Lecture 18: Indicator Variables and Interactions | Slides | Script |
| Lecture 19: Logistic Regression 1 | Slides | Script |
| Lecture 20: Logistic Regression 2 | Slides | Script |
| Lecture 21: Problems with p-values | Slides | Script |
| Lecture 22: Training and test sets | Slides | Script |
Short R help pages are available on a variety of topics: