Lectures and discussion notes

1. Lecture 1: Data exploration
2. Lecture 2: Visualization
3. Learn R with the birthday problem
4. Week 1 discussion section: Intro to R and tidyverse
5. Lecture 3: Intro to statistical inference
6. Lecture 4: Confidence intervals
7. Week 2 discussion section: Estimators
8. Lecture 5: The bootstrap
9. Lecture 6: Parametric inference
10. Week 3 discussion section (Part 1): The bootstrap
11. Week 3 discussion section (Part 2): Parametric inference
12. Lecture 7: Correlation
13. Lecture 8: Simple linear regression
14. Lecture 9: Uncertainty in regression and multiple regression
15. Lecture 10: Model evaluation and feature generation
16. Week 4 discussion section: Linear regression
17. Lecture 11: Logistic regression
18. Lecture 12: Classification error metrics
19. Week 5 discussion section: Logistic regression
20. Quiz Review Lecture
21. Lecture 13: Bias-variance tradeoff
22. Lecture 14: Regularization
23. Week 7 discussion section: Regularization
24. Lecture 15: Causal inference I
25. Lecture 15: Causal inference II
26. Week 8 discussion section: Extra project office hours
27. Quiz 2 Review Lecture

Lecture 1: Data exploration

Lecture 2: Visualization

Learn R with the birthday problem

The getting started with R video is also available via Panopto on Canvas.

Week 1 discussion section: Intro to R and tidyverse

Recordings of Discussion 1 are available via Panopto on Canvas.

Lecture 3: Intro to statistical inference

Annotated slides

Lecture 4: Confidence intervals

Annotated slides

Week 2 discussion section: Estimators

Recording on Canvas.

Lecture 5: The bootstrap

Annotated slides

Recording on Canvas.

Lecture 6: Parametric inference

Annotated slides

Recording on Canvas.

Week 3 discussion section (Part 1): The bootstrap

Recording on Canvas.

Week 3 discussion section (Part 2): Parametric inference

Recording on Canvas.

Lecture 7: Correlation

Annotated slides

Recording on Canvas.

Lecture 8: Simple linear regression

Annotated slides

Recording on Canvas.

Lecture 9: Uncertainty in regression and multiple regression

Annotated slides

Recording on Canvas.

Lecture 10: Model evaluation and feature generation

Annotated slides

Recording on Canvas.

Week 4 discussion section: Linear regression

Recording on Canvas.

Lecture 11: Logistic regression

Annotated slides

Recording on Canvas.

Lecture 12: Classification error metrics

Annotated slides

Recording on Canvas.

Week 5 discussion section: Logistic regression

Recording on Canvas.

Quiz Review Lecture

Notes on Ed.

Recording on Canvas.

Lecture 13: Bias-variance tradeoff

Annotated slides

Recording on Canvas.

Lecture 14: Regularization

Annotated slides

Recording on Canvas.

Week 7 discussion section: Regularization

Recording on Canvas.

Lecture 15: Causal inference I

Annotated slides

Lecture 15: Causal inference II

Annotated slides

Week 8 discussion section: Extra project office hours

No exercises this week.

Quiz 2 Review Lecture

Annotated slides

Recording on Canvas.