ST405 - Applied Nonparametric Statistics
- Prerequisites: [ST 422 and ST 430] or ST 511 or equivalent
- Term & Frequency: Every Fall
- Student Audience: Sophomore or higher students in Statistics and related fields. (In the same classroom as ST 505, but with some differences in grading)
- Credit: 3 credits
- Recent Texts: Introduction to Modern Nonparametric Statistics by J. J. Higgins, Duxbury (Thomson)
- Recent Instructors: Wenbin Lu
- 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.
- Alternatives: None
- Subsequent Courses: None
S1 2017 Sections:
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