ABSTRACT
The topics in this chapter are fundamental to the theory and application of Bayesian statistics. A well educated Bayesian should not be ignorant of them. The topics covered are statistical testing, exchangeability, likelihood functions, sufficient statistics, predictivism, Bayes factors and other model selection criteria, large sample normal approximations, consistency, hierarchical models, reference priors in the form of flat priors and Jeffreys’ priors, and some discussion of identifiability.
