This course takes a more theoretical look at estimation and hypothesis testing than MAT 254 (Statistical Models). Topics include maximum likelihood estimators (MLE’s), the information inequality, asymptotic theory of MLE’s, complete sufficient statistics, uniformly minimum variance unbiased estimators, likelihood ratio tests, most powerful tests, uniformly most powerful tests, and Bayesian statistics. Offered spring semesters irregularly.
