| 1 | Course Overview | |
| 2 | Statistical Models | |
| 3 | Bayesian Models | |
| 4 | Decision Theoretic Framework | Problem Set 1 due |
| 5 | Prediction | Problem Set 2 due |
| 6 | Sufficiency | |
| 7 | Exponential Families I | Problem Set 3 due |
| 8 | Exponential Families II | |
| 9 | Methods of Estimation I | Problem Set 4 due |
| 10 | Methods of Estimation II | |
| 11 | Bayes Procedures | Problem Set 5 due |
| 12 | Minimax Procedures | |
| 13 | Unbiased Estimation and Risk Inequalities | Problem Set 6 due |
| 14 | Convergence of Random Variables Probability Inequalities | |
| 15 | Limit Theorems | |
| 16 | Asymptotics I: Consistency and Delta Method | Take home exam 1 due |
| 17 | Asymptotics II: Limiting Distributions | |
| 18 | Asymptotics III: Bayes Inference and Large-Sample Tests | |
| 19 | Gaussian Linear Models | Problem Set 7 due |
| 20–25 | Generalized Linear Models | Problem Set 8 due & Problem Set 9 due |
| 26 | Case Study: Applying Generalized Linear Models | Take home exam 2 due |
