https://github.com/bgroenks96/bayes-workshop

Code and examples for "A Gentle Introduction to Bayesian Statistics and Modeling"
https://github.com/bgroenks96/bayes-workshop

Last synced: 27 days ago
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Code and examples for "A Gentle Introduction to Bayesian Statistics and Modeling"

• Host: GitHub
• URL: https://github.com/bgroenks96/bayes-workshop
• Owner: bgroenks96
• License: gpl-3.0
• Created: 2024-07-04T08:04:06.000Z (5 months ago)
• Default Branch: main
• Last Pushed: 2024-08-28T09:48:14.000Z (3 months ago)
• Last Synced: 2024-10-12T10:30:02.850Z (about 1 month ago)
• Language: Jupyter Notebook
• Size: 9.38 MB
• Stars: 2
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# A Gentle Introduction to Bayesian Statistics and Modeling

Code and examples for a workshop on Bayesian statistics and probabilistic programming.

## Resources for learning Bayesian statistics

Richard McElreath's [course](https://github.com/rmcelreath/stat_rethinking_2024) on "Statistical Rethinking"; variants of example code available in python (pymc), R, and Julia.

Andrew Gelman's book [Bayesdian Data Analysis](http://www.stat.columbia.edu/~gelman/book/).

Jose Storopoli's [online tutorial](https://storopoli.io/Bayesian-Julia/) using the Julia probabilistic programming language [Turing.jl](https://turinglang.org/).

Geir Evensen's book on [Data Assimilation Fundamentals](https://library.oapen.org/handle/20.500.12657/54434) for those interested in applying Bayesian stats to dynamical models.

If you have any further suggestions for resources to add here, please create an issue to let me know!