STATISTICAL INFERENCE

STA 732

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

Day / Time: 

WF 01:25 PM-02:40 PM

Location: 

Old Chem 025

Instructor: 

Ma, Li

Section: 

01