STA 732.01

Class Room: 
Allen 306
Class time: 
WF 01:25 PM-02:40 PM
Instructor: 
Ma, Li
Description: 
Classical, likelihood, and Bayesian approaches to statistical inference. Foundations of point and interval estimation, and properties of estimators (bias, consistency, efficiency, sufficiency, robustness). Testing: Type I and II errors, power, likelihood ratios; Bayes factors, posterior probabilities of hypotheses. The predictivist perspective. Applications include estimation and testing in normal models; model choice and criticism. Instructor: Berger, Li, Tokdar, or Wolpert
Course type: 
Graduate