Broadening its scope to nonstatisticians, Bayesian Methods for Data
Analysis, Third Edition provides an accessible introduction to the
foundations and applications of Bayesian analysis. Along with a
complete reorganization of the material, this edition concentrates
more on hierarchical Bayesian modeling as implemented via Markov
chain Monte Carlo (MCMC) methods and related data analytic
techniques. New to the Third Edition New data examples,
corresponding R and WinBUGS code, and homework problems Explicit
descriptions and illustrations of hierarchical modeling-now
commonplace in Bayesian data analysis A new chapter on Bayesian
design that emphasizes Bayesian clinical trials A completely
revised and expanded section on ranking and histogram estimation A
new case study on infectious disease modeling and the 1918 flu
epidemic A solutions manual for qualifying instructors that
contains solutions, computer code, and associated output for every
homework problem-available both electronically and in print Ideal
for Anyone Performing Statistical Analyses Focusing on applications
from biostatistics, epidemiology, and medicine, this text builds on
the popularity of its predecessors by making it suitable for even
more practitioners and students.
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