Bayesian Statistics

Modelling parameters as random variables

• Bayesian Inference

  Updating beliefs about parameters with data

• Priors

  Representing beliefs before data are observed

• Posterior Summaries

  Estimates, intervals and decisions from the posterior

• Computational Inference

  Approximating posteriors that cannot be found in closed form

• Model Choice

  Comparing, combining and checking models