Mathematical Theory of Bayesian Statistics: A Rigorous Yet Intuitive Introduction to Priors, Posteriors, and Asymptotics

This audiobook offers a comprehensive exploration of Bayesian statistics, guiding listeners through the mathematical foundations that turn probability into a precise logic of uncertainty. It covers key concepts such as priors, likelihoods, and posteriors, as well as advanced topics like decision theory, hierarchical models, and model evaluation, all presented with clarity and rigor. Designed for those seeking an in-depth understanding of formal data analysis, it aims to elevate your quantitative expertise and deepen your mastery of statistical inference.