Statistics 225 - Nonparametric Statistics

This course is an introduction to nonparametric and distribution-free statistical procedures and techniques. These methods rely heavily on counting and ranking techniques and will be explored through both theoretical and applied perspectives. One- and two-sample procedures will provide students with alternatives to traditional parametric procedures, such as the t-test. We will also investigate correlation, regression, and one-way analysis of variance techniques in a nonparametric setting. A variety of other topics may be explored in the nonparametric setting including resampling techniques (for example, bootstrapping), categorical data and contingency tables, density estimation, and the two-way layout. The course will emphasize data analysis (with appropriate use of statistical software) and the intuitive nature of nonparametric statistics. Four class hours per week. 

Requisite: STAT 111 or STAT 135 or equivalent. Spring semester.  Professor Wagaman.