Stat 210a: Theoretical Statistics
UC Berkeley
Offerings
Overview
An introduction to mathematical statistics, covering both frequentist and Bayesian aspects of modeling, inference, and decision-making. Topics include statistical decision theory; point estimation; minimax and admissibility; Bayesian methods; exponential families; hypothesis testing; confidence intervals; small and large sample theory; and M-estimation.
Logistics
Three hours of lecture per week.
Prerequisites
Linear algebra, real analysis, and a year of upper division probability and statistics.