Bobby's Teaching Page
BUS 41913 is a graduate course in Bayesian Inference. The course will focus on understanding the principles underlying Bayesian modeling and on building experience in the use of Bayesian analysis for making inference about real world problems. Particular attention will be paid to the computational techniques (e.g., MCMC) needed for most problems and their implementation in the R language for statistical computing.
Course syllabus (from Spring 2014; including required and recommended texts)
- This space will be populated with more material as Spring 2015 approaches.
Applied Regression Analysis
BUS 41100 (Sections 01, 02 and 085) is a course about regression, a powerful and widely used data analysis technique. Students will learn how to use regression to analyze a variety of complex real world problems. Heavy emphasis will be placed on analysis of actual datasets, and implementation in the R language for statistical computing. Topics covered include: simple linear regression, multiple regression, prediction, variable selection, residual diagnostics, time series (auto-regression), and classification (logistic regression).
- At this time, I am not scheduled to teach Applied Regression Analysis in the 2014-15 academic year.
Robert B. Gramacy -- 2014