Andrew Gelman
Wednesday, August 7: 4-5:30
Department of Statistics and Department of Political Science, Columbia University
Every philosophy has holes, and it is the responsibility of proponents of a philosophy to point out these problems. Here are a few holes in Bayesian data analysis: (1) flat priors immediately lead to terrible inferences about things we care about, (2) subjective priors are incoherent, (3) Bayes factors don’t work, (4) for the usual Cantorian reasons we need to check our models, but this destroys the coherence of Bayesian inference. Some of the problems of Bayesian statistics arise from people trying to do things they shouldn’t be trying to do, but other holes are not so easily patched.