R for Marketing Research and Analytics
Venue
Springer, New York (2015)
Publication Year
2015
Authors
Chris Chapman, Elea McDonnell Feit
BibTeX
Abstract
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.
