Nonparametric Statistics Semester: Spring Year: 2018 Subject Name: Statistics Course Number: 225 Institution: Amherst College 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 and regression 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 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 STAT 135. Limited to 24 students. Spring Semester. Professor Wagaman. Instructor Permission: Permission is required for interchange registration during the add/drop period only. Schedule #: STAT-225-01-1718S Course Sections Year - Any -2018201720162015201420132012 Term - Any -FallSpring Subject Course Number Institution - Any -Amherst CollegeHampshire CollegeMount Holyoke CollegeSmith CollegeUMass Amherst Section Number Nonparametric Statistics Sect # Credits Instructor(s) Instructor Email Meeting Times Location 01 4.0 Amy Wagaman awagaman@amherst.edu TTH 01:00PM-02:20PM; M 02:00PM-02:50PM SMUD 205; SMUD 205