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dc.contributor.authorChapman, Chris
dc.contributor.authorFeit, Elea McDonnell
dc.date.issued2019
dc.identifier.isbn978-3-030-14316-9
dc.identifier.urihttps://thuvienso.hoasen.edu.vn/handle/123456789/10401
dc.descriptionxx, 487 p. : ill.
dc.description.abstractThis 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.
dc.language.isoen
dc.publisherSpringer
dc.subjectMarketing
dc.subject.otherResearch
dc.subject.otherAnalytics
dc.titleR for marketing research and analytics
dc.typeBook
dc.description.version2nd edition


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