MATH 353 - Asymptotic Methods in Statistics with Applications

Modes of convergence for random variables and their distributions; central limit theorems; laws of large numbers; statistical large sample theory of functions of sample moments, sample quantiles, rank statistics, and extreme order statistics; asymptotically efficient estimation and hypothesis testing. Prerequisites: Math 251 and 252; linear algebra; undergraduate analysis (Math 231 and 232, or equivalent).
Units: 4
Course Type: Seminar