ABSTRACT

Since the publishing of Nolan and Temple Lang’s “Computing in the Statistics Curriculum” in 2010, the American Statistical Association issued new recommendations in the revised GAISE college report. To reflect modern practice and technologies, they emphasize giving students experience with multivariable thinking. Students develop multivariable thinking when they analyze real data in the context of investigating research questions of interest, which typically involve complex relationships between many variables. Proficiency in a statistical programming language facilitates the development of multivariable thinking by giving students tools to investigate complex data on their own. However, learning a programming language in an introductory course is difficult for many students. In this article, we recommend a set of computational skills for introductory courses, demonstrate them using R tidyverse, and describe a classroom activity to develop computational skills and multivariable thinking. We provide a tidyverse tutorial for introductory students, our course guide, and classroom activities. Supplementary materials for this article are available online at https://github.com/bryaneadams/Computational-Skills-for-Multivariable-Thinking-in-Introductory-Statistics.

摘要

自从Nolan和Temple Lang在2010年出版《统计课程中的计算》以来，美国统计协会在经修订的GAISE大学报告中发布了新的建议。为了反映现代实践和技术，他们强调为学生提供多变思维的经验。当学生在研究感兴趣的研究问题的背景下分析实际数据时，他们会发展出多变量思维，这通常涉及许多变量之间的复杂关系。统计编程语言的熟练程度通过为学生提供工具来自行研究复杂的数据，从而促进了多变量思维的发展。但是，对于许多学生而言，在入门课程中学习编程语言很困难。在本文中，我们为入门课程推荐一套计算技能，使用R tidyverse进行演示，并描述课堂活动以发展计算技能和多变量思维。我们为入门学生提供了整编教程，课程指南和课堂活动。可以在https://github.com/bryaneadams/Computational-Skills-for-Multivariable-Thinking-in-Introductory-Statistics在线获取本文的补充材料。