Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Chapman & Hall/CRC Texts in Statistical Science)
Description
This practical introduction to Bayesian statistical modeling guides readers from fundamental regression concepts to sophisticated multilevel and generalized linear models. Through step-by-step examples in R and Stan, it emphasizes computational thinking and helps readers understand how statistical models work rather than treating them as automated black boxes. The book explores Bayesian reasoning, maximum entropy, measurement error, missing data, spatial and network autocorrelation, and Gaussian process models, with a focus on making sound modeling choices and interpreting results responsibly. Clear, intuitive, and hands-on in style, it is designed for students and researchers seeking a deeper, more confident approach to statistical inference.
Available Editions
paperback
CRC Press LLC
Published Jan 1, 2015
487 pages
ISBN: 9781482253443
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Details
First Published
2015
Language
eng
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