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  • 标题:Supporting Data Science in the Statistics Curriculum
  • 本地全文:下载
  • 作者:Adam Loy ; Shonda Kuiper ; Laura Chihara
  • 期刊名称:Journal of Statistics Education
  • 电子版ISSN:1069-1898
  • 出版年度:2019
  • 卷号:27
  • 期号:1
  • 页码:2-11
  • DOI:10.1080/10691898.2018.1564638
  • 出版社:American Statistical Association
  • 摘要:This article describes a collaborative project across three institutions to develop, implement, and evaluate a series of tutorials and case studies that highlight fundamental tools of data science—such as visualization, data manipulation, and database usage—that instructors at a wide-range of institutions can incorporate into existing statistics courses. The resulting materials are flexible enough to serve both introductory and advanced students, and aim to provide students with the skills to experiment with data, find their own patterns, and ask their own questions. In this article, we discuss a tutorial on data visualization and a case study synthesizing data wrangling and visualization skills in detail, and provide references to additional class-tested materials. R and R Markdown are used for all of the activities.
  • 关键词:Data visualization ; Data wrangling ; R ; Relational databases ; Undergraduate curriculum
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