STAT 211: Statistical Inference

Received Certificate of Distinction in Teaching (Fall 2020)

Course abstract: Foundations of frequentist and Bayesian inference, and decision theory. Likelihood, sufficiency, and ancillarity. Point estimation, unbiasedness, maximum likelihood, method of moments, minimum-variance. Parametric and non-parametric hypothesis testing, confidence intervals. Selective inference: multiple testing, familywise error rate, false discovery rate. Bayesian inference, conjugate priors, credible intervals. Admissibility, Stein’s phenomenon, empirical Bayes. Time permitting: post-selection inference and the bootstrap.