Teaching material for Ben's Bayesian Statistics for the Social Sciences class.
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figures
models
tables
.gitignore
README.md
bayes.Rmd
bayes.html
brms_intro.R
brms_intro.Rmd
brms_intro.html
hierarchical_intro.Rmd
hierarchical_intro.html
mcmc.Rmd
mcmc.html
mcmc_code.R
priors.Rmd
priors.html
rstan_genquant.Rmd
rstan_genquant.html
rstan_intro.Rmd
rstan_intro.html
rstan_intro.zip
rstanarm_intro.Rmd
rstanarm_intro.html

README.md

Bayesian Statistics Teaching Material

This repository consists of some supplementary teaching material for the course, Bayesian Statistics for the Social Sciences, taught at Columbia University by Ben Goodrich.

  • Bayes' Theorem and Maximum Likelihood Estimation (bayes.*)
  • Priors and Sampling from the Grid (priors.*)
  • Markov Chain Monte Carlo Algorithms in Bayesian Statistics (mcmc.*)
  • A Brief Introduction to RStanARM (Model Fitting, Diagnostics, and Comparison) (rstanarm_intro.*)
  • Basic Hierarchical Regression in RStanARM (hierarchical_intro.*)
  • Brief Introduction to RStan (rstan_intro.*)
  • Generated Quantities in RStan (rstan_genquant.*)
  • Dealing with Missing Data