GitHub - nikhgarg/2023_ADBA

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Name		Name	Last commit message	Last commit date
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data		data
demos_ch11		demos_ch11
homework		homework
stan_code		stan_code
utilities_and_data		utilities_and_data
.gitignore		.gitignore
README.txt		README.txt
lecture2_binomial.ipynb		lecture2_binomial.ipynb
lecture2_binomial_pystan2.ipynb		lecture2_binomial_pystan2.ipynb
lecture3_normal.ipynb		lecture3_normal.ipynb
lecture3_regression.ipynb		lecture3_regression.ipynb
lecture4_sampling.ipynb		lecture4_sampling.ipynb
lecture6_7_hierarchicalmodel_debugging.ipynb		lecture6_7_hierarchicalmodel_debugging.ipynb
lecture7_mixtureofnormals.ipynb		lecture7_mixtureofnormals.ipynb

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This is the Spring 2023 course repo for "Applied Bayesian Data Analysis for Research", taught by Nikhil Garg at Cornell.
Course website: https://cs6384-orie6217.github.io/Spring2023/. 

The beginning lectures are heavily inspired by the following course by Aki Vehtari: Bayesian Data Analysis, https://avehtari.github.io/BDA_course_Aalto/. The demos and "utilities_and_data" folder are from the following repository, copied over and lightly modified for this class's purpose: https://github.com/avehtari/BDA_py_demos.

These lectures use PyStan3. It can be installed via pip: https://pypi.org/project/pystan/.