Bayesian Analysis for the Social Sciences
| Author | : | |
| Rating | : | 4.28 (876 Votes) |
| Asin | : | 0470011548 |
| Format Type | : | paperback |
| Number of Pages | : | 598 Pages |
| Publish Date | : | 2014-02-26 |
| Language | : | English |
DESCRIPTION:
“This is a comprehensive text on applied Bayesian statistics. Though it is primarily aimed at social scientists with strong computational and statistical backgrounds, its scope should appeal to a wider readership. I recommend it to anybody interested in actually applying Bayesian methods.” (Significance, 1 June 2010) "As in many texts, each chapter ends with a collection of exercises which would make this text suitable for teaching a one-semester course in Bayesian methods with applications in the social sciences with this small caveat, I was impressed with the text and believe it would be a worthy candidate for a first Bayesian courses that gives the student a balanced view of the theory and practice of Bayesian thinking." (The American Statistician, 1 February 2011)
Bayesian Analysis for the Social Sciences -- technical subject jde This 2009 text book on Bayesian Analysis at the graduate school level is the best I have ever seen, and is a welcomed addition to the literature. It is for serious "scholars" of statistics, applied statistics, and comples data analysis. It comes with code and examples ready for use in the R statistical computing environment.. Wonderful Examples SparseCodingFan This book makes difficult concepts accessible through lucid discussion and concrete examples. The examples make it easy to apply the techniques to ones own problems.. jose said Five Stars. Outstanding!!!, every proof is step by step.
The book is supported by a Website featuring WinBUGS and R code, and data sets.. This book provides an accessible introduction to Bayesian methods, tailored specifically for social science students. Bayesian methods are increasingly being used in the social sciences, as the problems encountered lend themselves so naturally to the subjective qualities of Bayesian methodology. It features examples of how to implement the methods using WinBUGS – the most-widely used Bayesian analysis software in the world – and R – an open-source statistical software. It contains lots of real examples from political science, psychology, sociology, and economics, exercises in all chapters, and detailed descriptions of all the key concepts, without assuming any background in statistics beyond a first course