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

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

Bayesian Statistics and Marketing 2/e

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)

利用這個尖端的統計工具包來微調您的市場研究

貝葉斯統計與市場行銷 展示了將貝葉斯方法應用於市場行銷中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、預測產品表現以及自訂目標行銷活動僅是貝葉斯方法承諾帶來革命性結果的幾個領域。本書提供了這一主題的全面且易於理解的概述，對於任何具統計知識的市場研究者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會發現，許多貝葉斯方法在社會科學問題中是至關重要的，這本書對這些方法進行了全面的探討。這包括對隨機係數模型、非參數方法以及內生性問題的計算挑戰的實用處理。

第二版的 貝葉斯統計與市場行銷 讀者還將發現：


  • 文本分析和機器學習中的貝葉斯方法討論

  • 反映最新研究和應用的更新

  • 現代統計軟體的討論，包括對 R 套件 bayesm 的介紹，該套件實現了本書中所有的模型

  • 廣泛的案例研究，將理論與實踐聯繫起來

貝葉斯統計與市場行銷 非常適合市場行銷、商業和經濟學系的高級學生和研究人員，以及任何具統計知識的市場從業者。

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)

彼得·羅西（Peter Rossi）是美國加州大學洛杉磯分校安德森管理學院的詹姆斯·柯林斯傑出大學市場營銷、經濟學和統計學教授。他是流行的 R 套件 bayesm 的作者，並在定價與促銷、目標市場營銷及其他相關主題上進行了廣泛的研究和發表。

格雷格·艾倫比（Greg Allenby）是美國俄亥俄州立大學費舍商學院的海倫·C·庫茲市場營銷教授及統計學教授。他是市場科學資訊學會和美國統計協會的院士，並在市場營銷中定量方法的發展與應用方面發表了廣泛的研究。

桑喬·米斯拉（Sanjog Misra）是美國芝加哥大學布斯商學院的查爾斯·H·凱爾斯塔特市場營銷教授。他曾擔任多本高影響力期刊的共同編輯，包括《定量市場營銷與經濟學》（Quantitative Marketing and Economics），其研究重點是利用機器學習和深度學習來研究消費者和企業的決策。

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