Taking Bayesian Inference Seriously [my talk tomorrow at Harvard conference on Big Data]

Mon 22 Aug, 9:50am, at Harvard Science Center Hall A:

Taking Bayesian Inference Seriously

Over the years I have been moving toward the use of informative priors in more and more of my applications. I will discuss several examples from theory, application, and computing where traditional noninformative priors lead to disaster, but a little bit of prior information can make everything work out. Informative priors also can resolve some of the questions of replication and multiple comparisons that have recently shook the world of science. It’s funny for me to say this, after having practiced Bayesian statistics for nearly thirty years, but I’m only now realizing the true value of the prior distribution.

8 thoughts on “Taking Bayesian Inference Seriously [my talk tomorrow at Harvard conference on Big Data]

  1. An alternative to the Bayesian testing is the chi-square goodness of fit test for proportions when the population priors are well known. I would appreciate a discussion on the differences between these two approaches.

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