This course introduces some of the key ideas of mathematical statistics related to the good performance and optimality of statistical procedures (parameter estimates and hypothesis tests) and covers many examples. The main objective is to learn how data arising from probability distributions with some unknown parameters can be used to narrow down or draw inferences about those unknown parameters. Students will learn how to construct optimal tests and estimators in many settings, particularly those involving normally distributed or large-sample data. Also listed as SURV 420.
1 course with a minimum grade of C- from (SURV410, STAT410).
Level of Rigor
Introduction to Mathematical Statistics, by R. Hogg & A.T. Craig
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Crosslisted with SURV420
Students interested in grad school in STAT should strongly consider this course