STAT 331 Nonparametric Statistical Methods

Students will learn introductory nonparametric statistical analysis including estimation and hypothesis testing. Key terminology in the discipline is explained. This course covers methods such as dichotomous data, one-, two-, and k-sample problems, and independence tests. Throughout the course, the efficiencies and the conditions for validity of the various methods are considered. Connections across settings are highlighted. While this course is intended to fulfill requirements in statistics and data science majors or minors, it may also be of interest to students with basic statistical understanding who would like to explore analysis of non-normal data. Data analysis in R is included.