Probability II for Statistics

3.0 credits · Graduate

This course will discuss several probabilistic results and techniques that are useful in mathematical statistics. Limit theorems and stochastic inequalities are two key components of the course. Topics to be covered include complements of basic limit theorems (Skorohod representation theorem, Berry-Esseen bound, Delta method), empirical distribution and quantile functions, U-statistics, bootstrap (and subsampling if time permits), stochastic convergence in metric spaces, and some elements of modern empirical process theory.