X

R for Marketing Research and Analytics (Use R!)

Product ID : 5930009


Galleon Product ID 5930009
Model
Manufacturer
Shipping Dimension Unknown Dimensions
I think this is wrong?
-
4,978

*Price and Stocks may change without prior notice
*Packaging of actual item may differ from photo shown

Pay with

About R For Marketing Research And Analytics

Product Description 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. Review “The monograph presents various numerous illustrations for R language, with setting the data, applying R codes, and interpreting the results obtained. It is written in a very friendly attitude to readers, giving an immediate practical guide to solving real marketing research problems.” (Stan Lipovetsky, Technometrics, Vol. 58 (3), August, 2016) “R for Marketing Research and Analytics is a clearly written, well-organized, comprehensive, and readable guide to using R … for marketing research and analytics. … For many readers―even for those who know R and have marketing research and analytics experience―this book can be a valuable resource. … used as a reference by marketing researchers and analysts, by engineering and business practitioners who wish to learn more about the analyses of customer and marketing data … .” (R. Jean Ruth, Interfaces, Vol. 46 (3), May-June, 2016) “The authors take care to guide the reader through the difficult task of data analysis of marketing data with R. … It is well written, in a colloquial and friendly tone. The reader often has the feeling that the authors talk directly to her. … I find the book to be a very welcome addition to the Use R! series and the marketing research and business analytics world. I can wholeheartedly recommend it … .” (Thomas Rusch, Journal of Statistical Software, Vol. 67 (2), October, 2015) Review "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"R for Marketing Research and Analytics provides an excellent introduction to the R statistical package for marketing researchers.  This is a must-have book for anyone who seriously pursues analytics in the field of marketing.  R is the software gold-standard in the research industry, and this book provides an introduction to R and shows how to run the analysis.  Topics range from graphics and exploratory methods to confirmatory methods including structural equation modeling, all illustrated with data.  A great contribution to th