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R for Marketing Research and Analytics / by Chris Chapman, Elea McDonnell Feit.

Springer Nature - Springer Mathematics and Statistics eBooks 2015 English International Available online

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Format:
Book
Author/Creator:
Chapman, Chris, Author.
Feit, Elea McDonnell., Author.
Series:
Use R!, 2197-5736
Language:
English
Subjects (All):
Statistics.
Marketing.
R (Computer program language).
Statistics for Business, Management, Economics, Finance, Insurance.
Statistics and Computing/Statistics Programs.
Local Subjects:
Statistics for Business, Management, Economics, Finance, Insurance.
Statistics and Computing/Statistics Programs.
Marketing.
Physical Description:
1 online resource (459 p.)
Edition:
1st ed. 2015.
Place of Publication:
Cham : Springer International Publishing : Imprint: Springer, 2015.
Language Note:
English
Summary:
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.
Contents:
Welcome to R
The R Language
Describing Data
Relationships Between Continuous Variables
Comparing Groups: Tables and Visualizations
Comparing Groups: Statistical Tests
Identifying Drivers of Outcomes: Linear Models
Reducing Data Complexity
Additional Linear Modeling Topics
Confirmatory Factor Analysis and Structural Equation Modeling
Segmentation: Clustering and Classification
Association Rules for Market Basket Analysis
Choice Modeling
Conclusion
Appendix: R Versions and Related Software
Appendix: Scaling up
Appendix: Packages Used
Index.
Notes:
Description based upon print version of record.
includes bibliographical references and index.
ISBN:
3-319-14436-7

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