Title:  Bayesian Statistics:  An Idea Whose Time Has Come

Presenter:  Dr. Brian J. Smith, University of Iowa

Today, the Bayesian approach to statistical modeling enjoys widespread acceptance in the statistical community.  Not only an academic endeavor, the approach is being applied to solve many real-world problems.  Bayesian methods are encouraged by the FDA for use in the development of medical devices and are being used to build more effective spam filters for e-mail.  The rise in popularity of these methods is surprising considering that their use was one of the most debated and controversial statistical topics no more than a decade ago.  We will look back at several advances that were key to the rise in popularity of Bayesian modeling.  Our talk will begin with the origin of Bayes Theorem and then move on to the development of the Metropolis-Hastings algorithm, the impact of high-speed computing, and the arrival of custom software for performing Bayesian analyses.