Applied Bayesian Analysis
A new class (Spring 2007) that I co-teach with Stanford Political Science colleague Simon Jackman is on applied Bayesian analysis in the social sciences. A working syllabus can be found on the course webpage.
Course Description (From the Stanford Bulletin)
ANTHSCI 254. Applied Bayesian Analysis (Same as POLISCI 354F.) Bayesian modeling in the social sciences emphasizing applications in political science, anthropological science, sociology, and education testing. Topics include: Bayesian computation via Markov chain Monte Carlo; Bayesian hierarchical modeling; Bayesian models for latent variables and latent states (measurement modeling); dynamic models; and Bayesian analysis of spatial models. Implementation of Bayesian approaches (priors, efficient sampling from posterior densities), data analysis, and model comparisons. Final project. Prerequisites: exposure to statistical modeling such as 200-level STATS or POLISCI 150/350B,C, or ANTHSCI 292. 3-5 units, Spr (Jones, J; Jackman, S)