Robert B. Gramacy Professor of Statistics

Bayesian Inference

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

Notices

  • The Final exam (datafile) was assigned on Wednesday 25 May. It is due Wednesday 8 June. Solutions: pdf and R code (glm and hierarchical glm)
  • The "Midterm" exam was Friday 13 May; solutions.
  • There was a short Quiz at the end of class on Friday 15 April.

Homework Due at the start of lecture

Computing

The recommended language for this course is R, which can be obtained from CRAN. Other languages such as MATLAB are allowed but are not recommended. Examples in lecture, and help in office hours, etc., will be exclusively in R. Below are some helpful R resources: