在统计学课程中支持数据科学

IF 2.2 Q3 Social Sciences Journal of Statistics Education Pub Date : 2019-01-02 DOI:10.1080/10691898.2018.1564638
A. Loy, Shonda Kuiper, Laura M. Chihara
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引用次数: 21

摘要

摘要本文描述了一个跨三个机构的合作项目,该项目旨在开发、实施和评估一系列教程和案例研究,这些教程和案例分析强调了数据科学的基本工具,如可视化、数据操作和数据库使用,各种机构的讲师可以将这些工具纳入现有的统计学课程中。由此产生的材料足够灵活,可以为入门级和高级学生提供服务,旨在为学生提供实验数据、找到自己的模式和提出自己的问题的技能。在本文中,我们详细讨论了一个关于数据可视化的教程和一个综合数据争论和可视化技能的案例研究,并提供了对其他经过类测试的材料的参考。R和R Markdown用于所有活动。
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Supporting Data Science in the Statistics Curriculum
Abstract 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.
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来源期刊
Journal of Statistics Education
Journal of Statistics Education EDUCATION, SCIENTIFIC DISCIPLINES-
CiteScore
1.20
自引率
0.00%
发文量
0
审稿时长
12 weeks
期刊介绍: The "Datasets and Stories" department of the Journal of Statistics Education provides a forum for exchanging interesting datasets and discussing ways they can be used effectively in teaching statistics. This section of JSE is described fully in the article "Datasets and Stories: Introduction and Guidelines" by Robin H. Lock and Tim Arnold (1993). The Journal of Statistics Education maintains a Data Archive that contains the datasets described in "Datasets and Stories" articles, as well as additional datasets useful to statistics teachers. Lock and Arnold (1993) describe several criteria that will be considered before datasets are placed in the JSE Data Archive.
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