Bayesian statistics for the social sciences /
Bridging the gap between traditional classical statistics and a Bayesian approach, David Kaplan provides readers with the concepts and practical skills they need to apply Bayesian methodologies to their data analysis problems. Part I addresses the elements of Bayesian inference, including exchangeab...
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| Format: | eBook |
| Language: | English |
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New York :
Guilford Publications,
2014.
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| Series: | Methodology in the social sciences.
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| Online Access: | Connect to the full text of this electronic book |
| Summary: | Bridging the gap between traditional classical statistics and a Bayesian approach, David Kaplan provides readers with the concepts and practical skills they need to apply Bayesian methodologies to their data analysis problems. Part I addresses the elements of Bayesian inference, including exchangeability, likelihood, prior/posterior distributions, and the Bayesian central limit theorem. Part II covers Bayesian hypothesis testing, model building, and linear regression analysis, carefully explaining the differences between the Bayesian and frequentist approaches. Part III extends Bayesian statistics to multilevel modeling and modeling for continuous and categorical latent variables. Kaplan closes with a discussion of philosophical issues and argues for an "evidence-based" framework for the practice of Bayesian statistics. Useful features for teaching or self-study: *Includes worked-through, substantive examples, using large-scale educational and social science databases. *Utilizes open-source R software programs available on the CRAN (such as MCMCpack and rjags); readers do not have to master the R language and can easily adapt the example programs to fit individual needs. *Shows readers how to carefully warrant priors on the basis of empirical data. *Companion website features data and code for the book's examples, plus other resources. |
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| Item Description: | "Series editor's note by Todd D. Little" - title page. Electronic resource. |
| Physical Description: | 1 online resource (xviii, 318 pages) : illustrations |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781462516667 (electronic bk.) 1462516661 (electronic bk.) |