Nonparametric and Robust Statistical Methods

Catalog description

Non-parametric statistical methods, including rank-based methods for testing location and dispersion for one-, two-, and more than two-sample designs, as well as non-parametric measures of association; robust estimation methods, with emphasis on robust analogs of the mean, standard deviation, and third-moment skewness. Students will be introduced to non-parametric resampling techniques (bootstrapping and permutation methods), which will be used with robust estimation to test hypotheses. Extensive use of computer-intensive estimation and hypothesis testing procedures. Prerequisite(s): STAT 7620 >= C and DATS 8170 >= C Lecture Hours: 3 Repeatability: May not be repeated for credit. Grade Mode: Normal, Audit Program Restrictions: DPHIL_BIOS, MS_BIOS Schedule Type (Primary): Lecture Click here for the Schedule of Classes.