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Bayesian Statistics and Marketing (Wiley Series in Probability and Statistics) (Englisch) Gebundene Ausgabe – 28. Oktober 2005


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Pressestimmen

"..an asset for business schools and marketing researchers." (Technometrics, May 2007) "'Bayesian Statistics and Marketing' comes from three pioneers in the field of market research and fills a hole in the existing literature on the topic." (Journal of the American Statistical Association, December 2006) "...extremely useful to both researchers and practitioners who are interested in understanding the power of these methods for solving important marketing problems." (Journal of Marketing, October 2006) "This book deserves to be widely adopted by business schools, and widely read by more numerate marketing practitioners." (Short Book Reviews, April 2006) " ... valuable to marketing researchers and others working on related applications, especially if they use advanced logistic and probit models." (JRSSA, Vol. 169, No. 4, October 2006) " ... an excellent book for researchers in applied Bayesian statistics." (Journal of Applied Statistics, Vol. 33: 9, 1034, November 2006) '...an important study tool for potential practitioners or all those researchers who study Bayesian methods through "learning by doing" (Statistical Papers,48,2007)

Synopsis

The past decade has seen a dramatic increase in the use of Bayesian methods in marketing due, in part, to computational and modelling breakthroughs, making its implementation ideal for many marketing problems. Bayesian analyses can now be conducted over a wide range of marketing problems, from new product introduction to pricing, and with a wide variety of different data sources. "Bayesian Statistics and Marketing" describes the basic advantages of the Bayesian approach, detailing the nature of the computational revolution. Examples contained in this book include household and consumer panel data on product purchases and survey data, demand models based on micro economic theory and random effect models used to pool data among respondents. The book also discusses the theory and practical use of MCMC methods.

Written by the leading experts in the field, this unique book: presents a unified treatment of Bayesian methods in marketing, with common notation and algorithms for estimating the models; provides a self contained introduction to Bayesian methods; includes case studies drawn from the authors' recent research to illustrate how Bayesian methods can be extended to apply to many important marketing problems; and is accompanied by an R package, bayesm, which implements all of the models and methods in the book and includes many datasets. In addition, the book's website hosts datasets and R code for the case studies. "Bayesian Statistics and Marketing" provides a platform for researchers in marketing to analyse their data with state of the art methods and develop new models of consumer behaviour. It provides a unified reference for cutting edge marketing researchers, as well as an invaluable guide to this growing area for both graduate students and professors, alike.

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Amazon.com: 4.8 von 5 Sternen 6 Rezensionen
10 von 10 Kunden fanden die folgende Rezension hilfreich
4.0 von 5 Sternen Not only marketing 18. Dezember 2010
Von Dimitri Shvorob - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
I will disagree with Eric on this book being a must-have for any "applied quantitative" statistics or marketing Ph.D. student, and call it a must-see for people interested in Bayesian discrete-choice modeling. The five case studies are all examples of marketing research, but are relevant to a much broader audience - consider, for example, "scale usage heterogeneity", affecting analysis of rating-scale responses. The case-study chapters are the book's forte, but it also offers a proper and rigorous introduction to Bayesian modeling, including the expected topics such as simulation (MCMC, Gibbs sampler, etc.) and linear regression, but also chapters on HLM, endogeneity, and model selection. The authors discuss doing Bayesian computation with R package bayesm, but regrettably relegate R material to appendices instead of integrating it into the main narrative and making implementation transparent and reproducible.

PS. In the "if you like this, you may like that" vein, a similar but more general book is "Bayesian statistical methods" by Congdon. (Also published by Wiley, and with a nearly identical cover).
24 von 39 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Rossi book is a must! 13. April 2006
Von Eric T. Bradlow - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe
Rossi, McCulloch, and Allenby is a must read for any applied

quantitative doctoral student in Marketing or Statistics. ?It provides

real applications, how to fit Bayesian models, and the challenges and

choices that the researcher faces. ?In summary, it is a book that

highlights and legitimizes the field of Bayesian Marketing as its own

and important discipline. ?We owe the authors a debt of gratitude.
0 von 1 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Five Stars 29. Januar 2016
Von Amazon Customer - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Very useful for phd students in marketing.
0 von 3 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Amazon book 22. Oktober 2012
Von Vicky - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
I was learning Bayesian statistics when a professor recommended this book to me, it is not very thick but all the stuff inside are handson and useful

would recommend to everybody.
0 von 3 Kunden fanden die folgende Rezension hilfreich
5.0 von 5 Sternen Difficulty but valuable 2. November 2012
Von Zhongjian Lin - Veröffentlicht auf Amazon.com
Format: Gebundene Ausgabe Verifizierter Kauf
Though difficulty for me, a outsider, I learn a lot of how to conduct bayesian analysis and what are important for this now famous approach.
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