Название: R For Marketing Research and Analytics, 2nd Edition Автор: Chris Chapman, Elea McDonnell Feit
Издательство: Springer
Серия: Use R!
ISBN: 3030143155
Год: 2019
Страниц: 492
Язык: английский
Формат: pdf (true)
Размер: 14.8 MB
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.
This book is designed for two audiences: practicing marketing researchers and analysts who want to learn R and students or researchers from other fields who wish to review selected marketing topics in an R context. This book will be particularly helpful to analysts who have some degree of programming experience and wish to learn R.
Contents:
Part I Basics of R
1 Welcome to R
2 An Overview of the R Language
Part II Fundamentals of Data Analysis
3 Describing Data
4 Relationships Between Continuous Variables
5 Comparing Groups: Tables and Visualizations
6 Comparing Groups: Statistical Tests
7 Identifying Drivers of Outcomes: Linear Models
Part III Advanced Marketing Applications
8 Reducing Data Complexity
9 Additional Linear Modeling Topics
10 Confirmatory Factor Analysis and Structural Equation Modeling
11 Segmentation: Clustering and Classification
12 Association Rules for Market Basket Analysis
13 Choice Modeling
14 Behavior Sequences
Conclusion 429
Appendix A: R Versions and Related Software
Appendix B: An Introduction to Reproducible Results with R Notebooks
Appendix C: Scaling Up
Appendix D: Packages Used
Appendix E: Online Materials and Data Files
References
Index 479
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