Spring Quarter 2013 Course Announcement STAT 425: Introduction to Nonparametric Statistics

Spring Quarter 2013 Course Announcement
STAT 425: Introduction to Nonparametric Statistics
Instructor: Fritz Scholz
Coverage: This course focuses on nonparametric and/or distribution free statistical
methods. The coverage follows the text by Lehmann with chapter headings:
1. Rank tests for comparing two treatments,
2. Comparing two treatments or attributes in a population model,
3. Blocked comparison for two treatments,
4. Paired comparison in a population model and the one-sample problem,
5. The comparison of more than two treatments,
6. Randomized complete blocks,
7. Tests of randomness and independence.
The k-sample Anderson-Darling test and its extension will be added in the discussion of
chapters 5 and 6. The statistical platform R will be used extensively to carry out these
tests and explore their power and large sample approximation properties. We may not
make it through the hole book.
Prerequisites: A basic introductory course of probability and statistics (e.g., Stat 342 or
Stat 390 or my consent) covering testing (type I and type II error, significance level, pvalue, power), confidence intervals, estimation, the essence of the central limit theorem
and knowledge or exposure to the statistical analysis platform R. If deemed appropriate
a short review of R will be given.
Text: Nonparametrics: Statistical Methods Based on Ranks (Paperback, 2006)
by Erich L. Lehmann, Springer Verlag (required).
A First Course in Statistical Programming with R
by W. John Braun and Duncan J. Murdoch, Cambridge University Press 2007 (optional).
R for Dummies
by Joris Meys and Andrie de Vries,
Wiley, June 2012, excellent introduction (optional).
Lecture slides and other materials will be provided in pdf file format.
Grade: Based on homework only.
Time & Place: Tuesday, Thursday 9:00-10:20 in Communications Bldg 226