An Update of the Most Popular Graduate-Level Introductions to Bayesian
Statistics for Social Scientists
Now that Bayesian modeling has become standard, MCMC is well understood
and trusted, and computing power continues to increase, Bayesian
Methods: A Social and Behavioral Sciences Approach, Third Edition
focuses more on implementation details of the procedures and less on
justifying procedures. The expanded examples reflect this updated
approach.
New to the Third Edition
- A chapter on Bayesian decision theory, covering Bayesian and
frequentist decision theory as well as the connection of empirical
Bayes with James-Stein estimation
- A chapter on the practical implementation of MCMC methods using the
BUGS software
- Greatly expanded chapter on hierarchical models that shows how this
area is well suited to the Bayesian paradigm
- Many new applications from a variety of social science disciplines
- Double the number of exercises, with 20 now in each chapter
- Updated BaM package in R, including new datasets, code, and procedures
for calling BUGS packages from R
This bestselling, highly praised text continues to be suitable for a
range of courses, including an introductory course or a
computing-centered course. It shows students in the social and
behavioral sciences how to use Bayesian methods in practice, preparing
them for sophisticated, real-world work in the field.