Learn to conduct: Prediction; Dealing with proportions; Discrete priors; Beta priors;
Single-parameter, normally distributed models with known means and unknown variance; Bayesian robustness; Mixtures of conjugate priors;
Multi-parameter models: Normal data with 2 unknown parameters; Comparing two proportions;

Bayesian computation: Monte carlo simulation; Model comparisons; Comparing hypotheses; Regression models: Normal linear regression; Prediction of future observations; and more.