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R For Marketing Research and Analytics [Use R!]

Sugarhouse Book Works
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Item specifics

Condition
Very Good: A book that does not look new and has been read but is in excellent condition. No obvious ...
ISBN
9783030143152
Subject Area
Computers, Business & Economics
Publication Name
R for Marketing Research and Analytics
Publisher
Springer International Publishing A&G
Item Length
9.3 in
Subject
Marketing / General, Mathematical & Statistical Software, Statistics, Marketing / Research
Publication Year
2019
Series
Use R! Ser.
Type
Textbook
Format
Trade Paperback
Language
English
Author
Elea Mcdonnell Feit, Chris Chapman
Item Weight
27.2 Oz
Item Width
6.1 in
Number of Pages
Xx, 487 Pages
Category

About this product

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030143155
ISBN-13
9783030143152
eBay Product ID (ePID)
20038411537

Product Key Features

Number of Pages
Xx, 487 Pages
Language
English
Publication Name
R for Marketing Research and Analytics
Publication Year
2019
Subject
Marketing / General, Mathematical & Statistical Software, Statistics, Marketing / Research
Type
Textbook
Subject Area
Computers, Business & Economics
Author
Elea Mcdonnell Feit, Chris Chapman
Series
Use R! Ser.
Format
Trade Paperback

Dimensions

Item Weight
27.2 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Edition Number
2
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
005.133
Table Of Content
Chapter 1: Welcom to R.- Chapter 2: An Overview of the R Language.- Chapter 3: Describing Data.- Chapter 4: Relationships Between Continuous Variables.- Chapter 5: Comparing Groups: Tables and Visualizations.- Chapter 6: Comparing Groups: Statistical Tests.- Chapter 7: Identifying Drivers of Outcomes: Linear Models.- Chapter 8: Reducing Data Complexity.- Chapter 9: Assorted Linear Modeling Topics.- Chapter 10: Confirmatory Factor Analysis and Structural Equation Modeling.- Chapter 11: Segmentation: Clustering and Classification.- Chapter 12: Association Rules for Market Basket Analysis.- Chapter 13: Choice Modeling.- Chapter 14: Marketing Mix Models.- Appendix A: R Versions and Related Software.- Appendix B: Scaling Up.- Appendix C: Packages Used.- Appendix D: Online Materials and Data Files.
Synopsis
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., Chapter 1: Welcom to R.- Chapter 2: An Overview of the R Language.- Chapter 3: Describing Data.- Chapter 4: Relationships Between Continuous Variables.- Chapter 5: Comparing Groups: Tables and Visualizations.- Chapter 6: Comparing Groups: Statistical Tests.- Chapter 7: Identifying Drivers of Outcomes: Linear Models.- Chapter 8: Reducing Data Complexity.- Chapter 9: Assorted Linear Modeling Topics.- Chapter 10: Confirmatory Factor Analysis and Structural Equation Modeling.- Chapter 11: Segmentation: Clustering and Classification.- Chapter 12: Association Rules for Market Basket Analysis.- Chapter 13: Choice Modeling.- Chapter 14: Marketing Mix Models.- Appendix A: R Versions and Related Software.- Appendix B: Scaling Up.- Appendix C: Packages Used.- Appendix D: Online Materials and Data Files.
LC Classification Number
QA276.4-.45

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Sugarhouse Book Works

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