I have been a professor in the Department of Mathematics and Statistics at Bowling Green State University since 1979.
Bayesian statistics is based on two ideas.
First, uncertainty about unknown quantities is expressed using the language of subjective probability, and, given new information or data, probabilities are updated using Bayes rule. I believe that Bayesian inferential methods have advantages over classical statistical procedures for a wide range of inferential problems. I'm particularly interested in developing inferential procedures for the class of generalized linear models. Recently, I've written papers on how to check the goodness of a model from a Bayesian viewpoint. The analysis of sports data.