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Bayesian Methods: A Social and Behavioral Sciences Approach (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences) - Tapa dura
Sinopsis
Book by Gill Jeff
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Críticas
"This book is a brilliant and importantly very accessible introduction to the concept and application of Bayesian approaches to data analysis. The clear strength of the book is in making the concept practical and accessible, without necessarily dumbing it down. The coverage is also remarkable." - Dr. S. V. Subramanian, Harvard School of Public Health "One of the signal contributions of Bayesian methods: A Social and Behavioral Sciences Approach is to reintroduce Bayesian inference and computing to a general social sciences audience. This is an important contribution--one that will make demand for this book highJeff Gill has gone some way toward reinventing the graduate-level methodology textbook Gill's treatment of the practicalities of convergence is a real servicenew users of the technique will appreciate this material. the inclusion of material on hierarchical modeling at first seems unconventional; its use in political science, while increasing, has been limited. However, Bayesian inference and MCMC methods are well-suited to these types of problems, and it is exactly these types of treatments that push the discipline in new directions. As noted, a number of monographs have appeared recently to reintroduce Bayesian inference to a new generation of computer-savvy statisticians. However, Gill achieves what these do not: a quality introduction and reference guide to Bayesian inference and MCMC methods that will become a standard in political methodology." -The Journal of Politics, November 2003
Reseña del editor
Despite increasing interest in Bayesian approaches, especially across the social sciences, it has been virtually impossible to find a text that introduces Bayesian data analysis in a manner accessible to social science students. The Bayesian paradigm is ideally suited to the type of data analysis they will have to perform, but the associated mathematics can be daunting.
Bayesian Methods: A Social and Behavioral Sciences Approach presents the basic principles of Bayesian statistics in a treatment designed specifically for students in the social sciences and related fields. Requiring few prerequisites, it first introduces Bayesian statistics and inference with detailed descriptions of setting up a probability model, specifying prior distributions, calculating a posterior distribution, and describing the results. This is followed by explicit guidance on assessing model quality and model fit using various diagnostic techniques and empirical summaries. Finally, it introduces hierarchical models within the Bayesian context, which leads naturally to Markov Chain Monte Carlo computing techniques and other numerical methods.
The author emphasizes practical computing issues, includes specific details for Bayesian model building and testing, and uses the freely available R and BUGS software for examples and exercise problems. The result is an eminently practical text that is comprehensive, rigorous, and ideally suited to teaching future empirical social scientists.
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- EditorialChapman and Hall/CRC
- Año de publicación2002
- ISBN 10 1584882883
- ISBN 13 9781584882886
- EncuadernaciónTapa dura
- IdiomaInglés
- Número de edición1
- Número de páginas480
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Bayesian Methods for the Social and Behavioral Sciences
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Bayesian Methods: A Social and Behavioral Sciences Approach (Chapman & Hall/CRC Statistics in the Social and Behavioral Sciences)
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