Statistics 225 - Nonparametric Statistics

This course is an introduction to nonparametric and distribution-free statistical procedures and techniques. These methods often rely 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. A variety of other topics may be explored in the nonparametric setting depending on the instructor. Potential topics include but are not limited to: nonparametric correlation and regression, resampling techniques (e.g. bootstrapping and permutation procedures), categorical data and contingency tables, density estimation, and the one-way and two-way layouts for analysis of variance. The course will emphasize data analysis (with appropriate use of statistical software) and the intuitive nature of nonparametric statistics.

Requisite: STAT 111 or MATH/STAT 135 or STAT 136 or equivalent. Limited to 24 students. Fall semester. Professor Wagaman. 

How to handle overenrollment: Priority for Statistics majors.

Students who enroll in this course will likely encounter and be expected to engage in the following intellectual skills, modes of learning, and assessment: quantitative work, problem sets, quizzes or exams, use of computational software, project