| Week | Date | Topic | Lecture slides | Lecture notes | R examples | Due |
|---|---|---|---|---|---|---|
| 1 | 2023-01-03 | Introduction to GLM | Lecture 1 | Lecture 1 | Data example 1 | – |
| 1 | 2023-01-05 | GLM concepts and estimation | Lecture 2 | Lecture 2 | – | – |
| 2 | 2023-01-10 | Statistical Inference for GLM | Lecture 3 | Lecture 3 | – | – |
| 2 | 2023-01-11 | – | – | – | – | HW1 due at 11:59pm |
| 2 | 2023-01-12 | Deviance Analysis | Lecture 4 | Lecture 4 | Data example 2 | – |
| 3 | 2023-01-17 | GLM computation, Binary models | Lecture 5 | Lecture 5 | Data example 3, part I | – |
| 3 | 2023-01-19 | Binary model applications, inference and computation | Lecture 6 | Lecture 6 | Data example 3, part II | – |
| 4 | 2023-01-24 | Multinomial GLM: nominal response | Lecture 7 | Lecture 7 | Data example 4, part I | – |
| 4 | 2023-01-25 | – | – | – | – | HW2 due at 11:59pm |
| 4 | 2023-01-26 | Multinomial GLM: ordinal response | Lecture 8 | Lecture 8 | Data example 4, part II | – |
| 5 | 2023-01-31 | GLM for counts: log-linear model and contingency tables | Lecture 9 | Lecture 9 | Data example 5 | – |
| 5 | 2023-02-02 | GLM for counts: over-dispersion and zero-inflation | Lecture 10 | Lecture 10 | Data example 6 | – |
| 6 | 2023-02-07 | Midterm Exam | – | – | – | – |
| 6 | 2023-02-09 | – | – | – | – | HW3 due at 11:59pm |
| 6 | 2023-02-09 | Beta-binomial GLM | Lecture 11 | Lecture 11 | – | – |
| 7 | 2023-02-14 | Quasi-likelihood, Sandwich estimator | Lecture 12 | Lecture 12 | Data example 7 | – |
| 7 | 2023-02-16 | Linear mixed effect models (LMM) | Lecture 13 | Lecture 13 | – | – |
| 8 | 2023-02-21 | Linear mixed effect models examples | – | Lecture 14 | Data example 8 | – |
| 8 | 2023-02-23 | Generalized linear mixed effect models examples | Lecture 15 | Lecture 15 | Data example 9 | – |
| 9 | 2023-02-27 | – | – | – | – | HW4 due at 11:59pm |