Statistics educators have long struggled with the fact that no traditional definition of probability is adequate for all purposes. Sometimes probability more naturally means frequency while at other times it lends itself to an interpretation as a degree of belief. However, if the latter, then why should the numerical rules of probability hold? How do we know when a probability is wrong?

In this talk, Aubrey Clayton (author of Bernoulli’s Fallacy) surveys the acrimonious history of these foundational questions and proposes a new approach to teaching probability-as-logic based on E. T. Jaynes’s principle of transformation groups.

The seminar was hosted by James King (Science Practice) and Emilie Rosenlund Soysal (London Mathematical Laboratory).