Course: STAT 34300
Title: Applied Linear Statistical Methods
Instructor(s): Rina Foygel Barber
Class Schedule: Sec 1: TR 3:30 PM-4:50 PM in E133
Textbook(s): Faraway, Linear Models with R, 2nd edition
Description: This course introduces the methods and applications of fitting and interpreting multiple regression models. The underlying distributional theory is discussed briefly. Topics include the examination of residuals, the transformation of data, strategies and criteria for the selection of a regression equation, and nonlinear models; categorical input variables (factors, constraints, and design matrices); factor models; factorial design; randomization; observational units versus experimental units; typology of experiments; randomized blocks design; and categorical responses (first case, logistic regression, likelihood analysis, and some basic asymptotic properties). The course emphasizes the use and interpretation of regression analysis with the R package. Techniques discussed are illustrated by examples involving both physical and social sciences data.