Probability review and one parameter models

Required:

• A First Course in Bayesian Statistical Methods by Peter D. Hoff.:
  • Section 2: Belief, probability and exchangeability
  • Section 3.1: The binomial model

Optional:

• Bayesian Data Analysis (Third Edition) by Andrew Gelman, John Carlin, Hal Stern, David Dunson, Aki Vehtari, and Donald Rubin.:
  • Section 1.4: Discrete probability examples: genetics and spell checking
  • Section 1.5: Probability as a measure of uncertainty
  • Section 1.8: Some useful results from probability theory
  • Section 2.1: Estimating a probability from binomial data
  • Section 2.2: Posterior as compromise between data and prior information
  • Section 2.3: Summarizing posterior inference
  • Section 2.4: Informative prior distributions
• Bayesian Computation with R (Second Edition) by Jim Albert:
  • Section 2: Introduction to Bayesian thinking