Readings, lectures, and videos

Each class session has a set of required readings that you should complete before attempting the tutorials.

1. Course Introduction
2. Introduction to R and RStudio
3. Data Visualization
4. Data Wrangling
5. Data Wrangling and Barplots
6. Causality
7. Randomized Experiments
8. Observational Studies
9. Summarizing Data
10. Survey Sampling
11. Bivariate Relationships and Functions
12. Joining and Tidying Data
13. Midterm Review and Prediction
14. Regression
15. Model Fit
16. Multiple Regression and Categorical Predictors
17. Sampling
18. Sampling Distributions
19. The Bootstrap
20. More Confidence Intervals
21. Hypothesis Testing
22. Two-sample Hypothesis Testing
23. Mathematical Models of Inference
24. Mathematical Models for Hypothesis Testing
25. Inference for Linear Regression