An Undergraduate Bayesian Statistics Course

  • Textbook: Probability and Bayesian Modeling (1st Edition), Albert and Hu, Chapman & Hall/CRC Texts in Statistical Science.

  • Computing resources

    • The ProbBayes R package

      • Installing from CRAN link
      install.packages("ProbBayes")
      library(ProbBayes)
      
      • Installing from Github
      devtools::install_github("bayesball/ProbBayes")
      require(ProbBayes)
      
    • JAGS (Just Another Gibbs Sampler)

      install.packages("runjags")
      require(runjags)
      
  • Pre-requisites

    • Coursework: college-level Multivariate Calculus, Linear Algebra, and Probability

    • Computing in R: equivalent to DataCamp's

  • Teaching and learning material (Fall 2019 iteration of MATH 347 Bayesian Statistics at Vassar College, NY)

    • Lectures folder: lecture files (.Rmd and .pdf).

    • Homework folder: homework files (.tex and .pdf).

    • Labs folder: lab files (.Rmd and .pdf).

    • Case Studies folder: case study files (.tex and .pdf).

    • Lecture recordings available at this complete YouTube playlist.