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Titlebook: R For Marketing Research and Analytics; Chris Chapman,Elea McDonnell‘Feit Book 2019Latest edition Springer Nature Switzerland AG 2019 R.St

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書目名稱R For Marketing Research and Analytics
編輯Chris Chapman,Elea McDonnell‘Feit
視頻videohttp://file.papertrans.cn/821/820005/820005.mp4
概述Introduces R specifically for marketing applications.Provides the background in R syntax necessary to accomplish immediate tasks.Includes updated R code and packages.Presents a complete approach to te
叢書名稱Use R!
圖書封面Titlebook: R For Marketing Research and Analytics;  Chris Chapman,Elea McDonnell‘Feit Book 2019Latest edition Springer Nature Switzerland AG 2019 R.St
描述.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 visua
出版日期Book 2019Latest edition
關(guān)鍵詞R; Statistics; Marketing research; Data science; Marketing analytics; Econometrics; Machine Learning; Compu
版次2
doihttps://doi.org/10.1007/978-3-030-14316-9
isbn_softcover978-3-030-14315-2
isbn_ebook978-3-030-14316-9Series ISSN 2197-5736 Series E-ISSN 2197-5744
issn_series 2197-5736
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Comparing Groups: Tables and Visualizationsc segment can best afford our product? Does the product appeal more to homeowners or renters? The answers help us to understand the market, to target customers effectively, and to evaluate the outcome of marketing activities such as promotions.
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Reducing Data Complexity might have many items on a consumer survey that reflect a smaller number of underlying concepts such as . with a service, . for a brand, or . for a product. If we can reduce the data to its underlying dimensions, we can more clearly identify the underlying relationships among concepts.
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