Statistics

ST505 - Applied Nonparametric Statistics

• Prerequisites: ST421-422 (or ST371-372), or ST511
• Term & Frequency: Every spring
• Student Audience: Sophomore or higher students in Statistics and related fields
• Credit: 3 credits
• Recent Texts: Introduction to Modern Nonparametric Statistics by J. J. Higgins, Duxbury (Thomson)
• Recent Instructors: Huixia Judy Wang
• Background and Goals: The course provides an introduction to statistical estimation and inference methods that require relatively mild assumptions about the population distribution. The course uses software R and will cover some basics of R programming.
• Content: Classical nonparametric hypothesis testing methods for one sample, two samples and multiple samples, Spearman and Kendall correlation coefficients, permutation tests, bootstrap methods, and nonparametric regression.
• Alternatives: None
• Subsequent Courses: None

SP 2013 Sections: