R for Marketing Research and Analytics
暫譯: R 在行銷研究與分析中的應用

Chapman, Chris, Feit, Elea McDonnell

R for Marketing Research and Analytics

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商品描述

The 2nd edition of R for Marketing Research and Analytics continues to be the best place to learn R for marketing research. This book is a complete introduction to the power of R for marketing research practitioners. The text describes statistical models from a conceptual point of view with a minimal amount of mathematics, presuming only an introductory knowledge of statistics. Hands-on chapters accelerate the learning curve by asking readers to interact with R from the beginning. Core topics include the R language, basic statistics, linear modeling, and data visualization, which is presented throughout as an integral part of analysis.

Later chapters cover more advanced topics yet are intended to be approachable for all analysts. These sections examine logistic regression, customer segmentation, hierarchical linear modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a minimally complex approach, demonstrating and explaining Bayesian methods alongside traditional analyses for analysis of variance, linear models, and metric and choice-based conjoint analysis.

With its emphasis on data visualization, model assessment, and development of statistical intuition, this book provides guidance for any analyst looking to develop or improve skills in R for marketing applications.

The 2nd edition increases the book's utility for students and instructors with the inclusion of exercises and classroom slides. At the same time, it retains all of the features that make it a vital resource for practitioners: non-mathematical exposition, examples modeled on real world marketing problems, intuitive guidance on research methods, and immediately applicable code.

商品描述(中文翻譯)

《R for Marketing Research and Analytics》第二版仍然是學習行銷研究中 R 語言的最佳選擇。本書是行銷研究從業者使用 R 的完整入門指南。文本從概念的角度描述統計模型，數學內容極少，僅假設讀者具備基本的統計知識。實作章節通過要求讀者從一開始就與 R 互動，加速學習曲線。核心主題包括 R 語言、基本統計、線性模型和資料視覺化，這些內容貫穿於分析的整體過程中。

後面的章節涵蓋了更高級的主題，但仍然旨在讓所有分析師都能輕鬆理解。這些部分探討了邏輯回歸、客戶細分、階層線性模型、市場籃分析、結構方程模型和 R 中的聯合分析。文本獨特地以簡單的方式呈現貝葉斯模型，展示並解釋貝葉斯方法，並與傳統的變異數分析、線性模型以及基於度量和選擇的聯合分析進行比較。

本書強調資料視覺化、模型評估和統計直覺的發展，為任何希望在行銷應用中發展或改善 R 技能的分析師提供指導。

第二版通過加入練習題和課堂投影片，增加了本書對學生和教師的實用性。同時，它保留了所有使其成為從業者重要資源的特點：非數學的闡述、基於真實行銷問題的範例、對研究方法的直觀指導，以及可立即應用的程式碼。

作者簡介

Chris Chapman PhD is a Principal Quantitative Researcher at Google, and an author of Chapman & Feit, R for Marketing Research and Analytics (Springer, 2015). In the broader industry, he is chair of the 2017 Advanced Research Techniques Forum, past President of the American Marketing Association's Practitioner Council, and a member of several other conference and industry committees. Chris is the internal "conjoint analysis evangelist" at Google, and an enthusiastic contributor to the quantitative marketing community outside, where he regularly presents research innovations and teaches workshops on R, conjoint analysis, strategic modeling, and other analytics topics.

Elea McDonnell Feit is an Assistant Professor of Marketing at Drexel University and a Senior Fellow of Marketing at The Wharton School. She enjoys making quantitative methods accessible to a broad audience and teaches workshops and courses on advertising measurement, marketing experiments, marketing analytics in R, discrete choice modeling and hierarchical Bayes methods. She is active in the organizing committees for practitioner conferences including AMA Advanced Research Techniques Forum and INFORMS Business Analytics and is an author of Chapman & Feit, R for Marketing Research and Analytics (Springer, 2015).

作者簡介(中文翻譯)

Chris Chapman 博士 是 Google 的首席量化研究員，也是 Chapman & Feit 的著作 R for Marketing Research and Analytics（Springer, 2015）的作者。在更廣泛的行業中，他是 2017 年高級研究技術論壇的主席，曾任美國行銷協會實務委員會的會長，並且是其他幾個會議和行業委員會的成員。Chris 是 Google 內部的「聯合分析傳道者」，並且熱衷於為外部的量化行銷社群做出貢獻，定期發表研究創新並教授有關 R、聯合分析、策略建模及其他分析主題的工作坊。

Elea McDonnell Feit 是德雷克塞大學的行銷助理教授，也是沃頓商學院的行銷高級研究員。她喜歡讓量化方法對廣泛的受眾變得可及，並教授有關廣告測量、行銷實驗、R 中的行銷分析、離散選擇建模和階層貝葉斯方法的工作坊和課程。她活躍於實務會議的組織委員會，包括 AMA 高級研究技術論壇和 INFORMS 商業分析，並且是 Chapman & Feit 的著作 R for Marketing Research and Analytics（Springer, 2015）的作者。

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