Anthropological Sciences 254/Political Science 354F: Applied Bayesian Analysis

Instructors: Simon Jackman and James Holland Jones

Description

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

Syllabus

Readings

Many of the readings for this class are available online in electronic format and can be found in this restricted directory.

Handouts

This restricted directory holds the various hand-outs (e.g., lecture notes, supplementary readings, etc.) that we will accumulate throughout the quarter.

Code, Data, etc.

This restricted directory will hold the R/BUGS/JAGS code and data files that we accumulate over the quarter

Links

This page contains pointers to resources for practical Bayesian analysis for the social and biological sciences.

Last Modified: 04.03.07