Mathematical Statistics

This specialization covers the theory that statistical practice rests on: probability spaces and measure-theoretic foundations, random variables and distribution theory, transformations and sampling distributions, modes of convergence and limit theorems, point and interval estimation with sufficiency, unbiasedness, efficiency and maximum likelihood, the Neyman-Pearson framework for testing, Bayesian inference, and decision theory. It is a proof-based course rather than a methods one.