MATH 455 - Mathematical Statistics

An important course for students considering graduate work in statistics or biostatistics, this course explores the mathematics underlying modern statistical applications. Topics include: classical techniques for parameter estimation and evaluation of estimator properties, hypothesis testing, confidence intervals, and linear regression. Special topics vary and may include: tests of independence, resampling techniques, introductory Bayesian concepts, and non-parametric methods. Though not the focus of this course, concepts will be highlighted through applications in a variety of settings. Prerequisite(s): MATH 354 Even numbered spring semesters. (4 Credits)