| 書目名稱 | R For Marketing Research and Analytics |
| 編輯 | Chris Chapman,Elea McDonnell‘Feit |
| 視頻video | http://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 |  |
| 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 |
| 關鍵詞 | R; Statistics; Marketing research; Data science; Marketing analytics; Econometrics; Machine Learning; Compu |
| 版次 | 2 |
| doi | https://doi.org/10.1007/978-3-030-14316-9 |
| isbn_softcover | 978-3-030-14315-2 |
| isbn_ebook | 978-3-030-14316-9Series ISSN 2197-5736 Series E-ISSN 2197-5744 |
| issn_series | 2197-5736 |
| copyright | Springer Nature Switzerland AG 2019 |
|Archiver|手機版|小黑屋|
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