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R for Marketing Research and Analytics (Use R!)
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“Very good condition spotless pages see pictures attached”
Very good
A book that does not look new and has been read but is in excellent condition. No obvious damage to the cover, with the dust jacket (if applicable) included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See the seller’s listing for full details and description of any imperfections.
- Buy It NowR for Marketing Research and Analytics (Use R!)
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Located in: Anaconda, Montana, United States
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eBay item number:225929132552
Item specifics
- Condition
- Very good
- Seller notes
- “Very good condition spotless pages see pictures attached”
- ISBN
- 9783319144351
About this product
Product Identifiers
Publisher
Springer International Publishing A&G
ISBN-10
3319144359
ISBN-13
9783319144351
eBay Product ID (ePID)
208589631
Product Key Features
Number of Pages
Xviii, 454 Pages
Language
English
Publication Name
R for Marketing Research and Analytics
Publication Year
2015
Subject
Marketing / General, Mathematical & Statistical Software, Statistics, Marketing / Research
Type
Textbook
Subject Area
Computers, Business & Economics
Series
Use R! Ser.
Format
Trade Paperback
Dimensions
Item Weight
280 Oz
Item Length
9.3 in
Item Width
6.1 in
Additional Product Features
Intended Audience
Scholarly & Professional
Reviews
"R for Marketing Research and Analytics is the perfect book for those interested in driving success for their business and for students looking to get an introduction to R. While many books take a purely academic approach, Chapman (Google) and Feit (Formerly of GM and the Modellers) know exactly what is needed for practical marketing problem solving. I am an expert R user, yet had never thought about a textbook that provides the soup-to-nuts way that Chapman and Feit: show how to load a data set, explore it using visualization techniques, analyze it using statistical models, and then demonstrate the business implications. It is a book that I wish I had written." Eric Bradlow , K.P. Chao Professor, Chairperson, Wharton Marketing Department and Co-Director, Wharton Customer Analytics Initiative "Chris Chapman's and Elea Feit's engaging and authoritative book nicely fills a gap in the literature. At last we have an accessible book that presents core marketing research methods using the tools and vernacular of modern data science. The book will enable marketing researchers to up their game by adopting the R statistical computing environment. And data scientists with an interest in marketing problems now have a reference that speaks to them in their language." James Guszcza , Chief Data Scientist, Deloitte - US
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
005.133
Table Of Content
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.
Synopsis
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.
LC Classification Number
QA276-280
Item description from the seller
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- 19 Jan, 2020
Good stuff
Verified purchase: YesCondition: Pre-ownedSold by: textbooks_source
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