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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Bibliographic Details
Main Author: Kaplan, David 1955- (Author)
Format: Electronic eBook
Language:English
Published: New York Guilford Publications 2014
Series:Methodology in the social sciences
Subjects:
Online Access:UBG01
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 statis
Item Description:Description based upon print version of record
Physical Description:1 Online-Ressource (xviii, 318 Seiten) Diagramme
ISBN:9781462516513

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