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  • 标题:Introducing Data Science Techniques by Connecting Database Concepts and dplyr
  • 本地全文:下载
  • 作者:Jennifer E. Broatch ; Suzanne Dietrich ; Don Goelman
  • 期刊名称:Journal of Statistics Education
  • 电子版ISSN:1069-1898
  • 出版年度:2019
  • 卷号:27
  • 期号:3
  • 页码:147-153
  • DOI:10.1080/10691898.2019.1647768
  • 出版社:American Statistical Association
  • 摘要:Early exposure to data science skills, such as relational databases, is essential for students in statistics as well as many other disciplines in an increasingly data driven society. The goal of the presented pedagogy is to introduce undergraduate students to fundamental database concepts and to illuminate the connection between these database concepts and the functionality provided by the dplyr package for R. Specifically, students are introduced to relational database concepts using visualizations that are specifically designed for students with no data science or computing background. These educational tools, which are freely available on the Web, engage students in the learning process through a dynamic presentation that gently introduces relational databases and how to ask questions of data stored in a relational database. The visualizations are specifically designed for self-study by students, including a formative self-assessment feature. Students are then assigned a corresponding statistics lesson to utilize statistical software in R within the dplyr framework and to emphasize the need for these database skills. This article describes a pilot experience of introducing this pedagogy into a calculus-based introductory statistics course for mathematics and statistics majors, and provides a brief evaluation of the student perspective of the experience. Supplementary materials for this article are available online.
  • 关键词:Data science ; Databases ; Education ; Teaching tool
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