Stat 151a: Linear Modelling: Theory and Applications
UC Berkeley
Offerings
Overview
A coordinated treatment of linear and generalized linear models and their application. Linear regression, analysis of variance and covariance, random effects, design and analysis of experiments, quality improvement, log-linear models for discrete multivariate data, model selection, robustness, graphical techniques, productive use of computers, in-depth case studies. This course uses either R or Python as its primary computing language, as determined by the instructor.
Logistics
Three hours of Lecture and Two hours of Laboratory per week for 15 weeks.
Prerequisites
STAT 135. STAT 133 recommended.