R for marketing research and analytics.

• Main Author: Chris Chapman, Elea McDonnell Feit.
• Format: Book
• Language: English
• Published: Spinger 2020
• Subjects: Marketing.
• Online Access: http://dspace.uniten.edu.my/jspui/handle/123456789/17771

R is a great choice for marketing analysts. It offers unsurpassed capabilities for fitting statistical models. It is extensible and is able to process data from many different systems, in a variety of forms, for both small and large data sets. The R ecosystem includes the widest available range of established and emerging statistical methods as well as visualization techniques. Yet the use of R in marketing lags other fields such as statistics, econometrics, psychology, and bioinformatics.With your help, we hope to change that! This book is designed for two audiences: practicing marketing researchers and analysts who want to learn R, and students or researchers from other fields who want to review selected marketing topics in an R context. What are the prerequisites? Simply that you are interested in R for marketing, are conceptually familiar with basic statistical models such as linear regression, and are willing to engage in hands-on learning. This book will be particularly helpful to analysts who have some degree of programming experience and wish to learn R. In Chap. 1 we describe additional reasons to use R (and a few reasons perhaps not to use R). The hands-on part is important. We teach concepts gradually in a sequence across the first seven chapters and ask you to type our examples as you work; this book is not a cookbook-style reference. We spend some time (as little as possible) in Part I on the basics of the R language and then turn in Part II to applied, real-world marketing analytics problems. Part III presents a few advanced marketing topics. Every chapter shows off the power of R, and we hope each one will teach you something new and interesting.