TITLE: Proving de Finetti's Representation Theorem with Ergodicity

 

ABSTRACT: In this talk, I will give a survey of my recent and ongoing research. I will then present a new simplified proof of Bruno de Finetti's representation theorem for exchangeable Bernoulli random variables. de Finetti's theorem is an important foundational result for Bayesian analysis that encapsulates key differences between Bayesian and frequentist approaches to statistics. This proof serves to increase the result's accessibility to the wider statistical community, and to provide a more intuitive understanding of what it accomplishes.