In Statistics 408 / 608, we cover multiple, curvilinear, and logistic regression analysis,
along with regression diagnostics, transformations, and analysis of covariance.
Prerequisites include Stat 601, 641, 651, or 212 (a prior course in inferential statistics,
including calculating and interpreting confidence intervals, hypothesis tests, and simple linear regression as well as finding expected values and variances); three semesters of calculus;
and a linear algebra course such as Math 304.
Gradebook, discussion board, videos, and class notes are posted here.
Information on the course textbook, including data sets and code.
(PDF) The course syllabus for Spring 2018.