The following course is a shortened version of rmcelreath/stat_rethinking_2020, which covers the first 6 weeks.
Statistical Rethinking 2nd Edition.
The lectures can be found at YouTube: Statistical Rethinking 2019
We'll use Python and specifically PyMC3 throughout.
Consider using Colab notebooks if you don't want to setup a python environment. It's free online Python notebooks.
- Before class: Read chapters and watch lectures. Important: Read the corresponding PyMC3 code examples alongside the book chapters.
- In class: Solve exercises.
- After class: Peer grade exercises.
Expected Workload:
- Reading: 3 hours.
- Watching lectures: 2 hours
- Exercises in class: 4 hours
- Peer Grading: 1 hour
Total: 10 hours/week.
| Week # | Reading | Lectures | Exercise |
|---|---|---|---|
| 1 | Chapters 1, 2 and 3 | The Golem of Prague <slides> <video> Garden of Forking Data <slides> <video> |
week1.md |
| 2 | Chapter 4 | Geocentric Models <slides> <video> Wiggly Orbits <slides> <video> |
week2.md |
| 3 | Chapters 5 and 6 | Spurious Waffles <slides> <video> Haunted DAG <slides> <video> |
week3.md |
| 4 | Chapter 7 | Ulysses' Compass <slides> <video> Model Comparison <slides> <video> |
week4.md |
| 5 | Chapters 8 and 9 | Conditional Manatees <slides> <video> Markov Chain Monte Carlo <slides> <video> |
week5.md |