Lessons

Lesson 0: Setting up computing resources
Lesson 1: Introduction to Bayesian modeling
Lesson 2: Parameter estimation by optimization
Lesson 3: Markov chain Monte Carlo and Stan
Lesson 4: Display of MCMC results and diagnostics
Lesson 5: Prior and posterior predictive checks
Lesson 6: Hierarchical models
Lesson 7: Principled pipelines

Exercises

Exercise 1. Practice with Bayesian modeling
Exercise 2. Paremeter estimation by optimization
Exercise 3. First foray into MCMC
Exercise 4: More Bayesian inference with MCMC
Exercise 5: Bayesian modeling with prior and posterior predictive checks
Exercise 6: Hierarchical models
Exercise 7: Principled pipelines

Schedule

Schedule overview
Daily schedule

PoL workshop on statistical inference, part 2

Lesson 0: Setting up computing resources
| Download notebook

Lesson 0: Setting up computing resources

To set up your computer, follow the instructions for part 1 of the workshop.

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Last updated on Aug 12, 2024.

© 2021–2024 Justin Bois. With the exception of pasted graphics, where the source is noted, this work is licensed under a Creative Commons Attribution License CC-BY 4.0. All code contained herein is licensed under an MIT license.

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