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.
