Bayesian Statistics and Marketing 2/e (貝葉斯統計與行銷(第二版))

Rossi, Peter E., Allenby, Greg M., Misra, Sanjog

相關主題

商品描述

Fine-tune your marketing research with this cutting-edge statistical toolkit

Bayesian Statistics and Marketing illustrates the potential for applying a Bayesian approach to some of the most challenging and important problems in marketing. Analyzing household and consumer data, predicting product performance, and custom-targeting campaigns are only a few of the areas in which Bayesian approaches promise revolutionary results. This book provides a comprehensive, accessible overview of this subject essential for any statistically informed marketing researcher or practitioner.

Economists and other social scientists will find a comprehensive treatment of many Bayesian methods that are central to the problems in social science more generally. This includes a practical approach to computationally challenging problems in random coefficient models, non-parametrics, and the problems of endogeneity.

Readers of the second edition of Bayesian Statistics and Marketing will also find:

  • Discussion of Bayesian methods in text analysis and Machine Learning
  • Updates throughout reflecting the latest research and applications
  • Discussion of modern statistical software, including an introduction to the R package bayesm, which implements all models incorporated here
  • Extensive case studies throughout to link theory and practice

Bayesian Statistics and Marketing is ideal for advanced students and researchers in marketing, business, and economics departments, as well as for any statistically savvy marketing practitioner.

商品描述(中文翻譯)

用這個尖端的統計工具包來精進您的市場研究

《Bayesian Statistics and Marketing》展示了在市場研究中應用貝葉斯方法解決一些最具挑戰性和重要性問題的潛力。分析家庭和消費者數據、預測產品表現和定制目標廣告活動只是貝葉斯方法在這些領域中所承諾的革命性結果的一部分。本書提供了一個全面、易於理解的概述,對於任何具有統計學知識的市場研究人員或從業者來說都是必不可少的。

經濟學家和其他社會科學家將找到許多貝葉斯方法的全面介紹,這些方法對於社會科學中的問題非常重要。這包括對於隨機係數模型、非參數方法和內生性問題等計算上具有挑戰性的問題的實用方法。

《Bayesian Statistics and Marketing》第二版的讀者還將找到:

- 對於文本分析和機器學習中的貝葉斯方法的討論
- 反映最新研究和應用的全面更新
- 對現代統計軟件的討論,包括介紹實現所有模型的R軟件包bayesm
- 通過廣泛的案例研究將理論與實踐聯繫起來

《Bayesian Statistics and Marketing》非常適合市場、商業和經濟學系的高級學生和研究人員,以及任何具有統計學知識的市場營銷從業者。

作者簡介

Peter Rossi is James Collins Distinguished University Professor of Marketing, Economics, and Statistics at the Anderson School of Management, UCLA, USA. He is the author of the popular R package, bayesm, and he has researched and published extensively on pricing and promotion, target marketing, and other related subjects.

Greg Allenby is Helen C. Kurtz Professor of Marketing as well as Professor of Statistics at the Fisher College of Business, Ohio State University, USA. He is a Fellow of the Informs Society for Marketing Science and the American Statistical Association, and he has published widely on the development and application of quantitative methods in marketing.

Sanjog Misra is Charles H. Kellstadt Professor of Marketing in the Booth School of Business, University of Chicago, USA. He has served as the co-editor of numerous high-impact journals, including Quantiative Marketing and Economics, and his research focuses on the use of machine learning and deep learning to study consumer and firm decisions

作者簡介(中文翻譯)

Peter Rossi是加州大學洛杉磯分校安德森管理學院的詹姆斯·柯林斯卓越大學教授,專攻於市場營銷、經濟學和統計學。他是知名的R語言套件bayesm的作者,並在定價和促銷、目標市場營銷等相關主題上進行了廣泛的研究和發表。

Greg Allenby是俄亥俄州立大學費舍爾商學院的海倫·庫爾茨市場營銷教授和統計學教授。他是Informs市場科學學會和美國統計學會的會士,並在市場營銷中的量化方法的發展和應用方面發表了大量的論文。

Sanjog Misra是芝加哥大學布斯商學院的查爾斯·凱爾斯塔特市場營銷教授。他曾擔任多個高影響力期刊的共同編輯,包括《量化市場營銷和經濟學》,他的研究重點是使用機器學習和深度學習研究消費者和企業的決策。