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Statistical Rethinking: A Bayesian Course Using Python and NumPyro



This repo contains the python/numpyro version of the Statistical Rethinking course that Professor Richard McElreath taught on the Max Planck Institute for Evolutionary Anthropology in Leipzig during the Winter of 2019/2020. The original repo for the course, from which this repo is forked, can be found here. The course contains 20 lectures structured in 10 weeks with a series of assignments for each week. The course is an excellent introduction to bayesian modelling in general and to the Rethinking Statistics wonderful book written by Professor McElreath.

The present work is a derivative of Statistical Rethinking: A Bayesian Course Using python and pymc3 by Gabriel Bosque Chacon. He did an incredible work doing the PyMC3 version of the Statistical Rethinking course. I made the numpyro code, the seaborn figures and very minor modifications to their comments.

How to use this repo

All the notebooks can be interactively used through the "launch binder" button located in the top of this file. There are ten jupyter notebooks, one for each week of the course. At the beginning of each notebook there are links to the youtube videos of the lectures, the slides used and the original homework questions and answers in R.

This repo is recommended to be used as follows:

  1. Go to the notebook of the week.
  2. Watch the two videos for the lectures of that week.
  3. Read the original problems presented to the students and try to solve them on your own.
  4. Follow the exercises solutions of the notebook with my code and explanations by Professor McElreath.


Statistical Rethinking: A Bayesian Course Using Python and NumPyro







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