Computational Skills for Multivariable Thinking in Introductory Statistics

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.

KEYWORDS:

• Classroom activity
• COVID-19
• Censorship
• Statistical computing

Acknowledgments

We thank our West Point colleagues Krista Watts, Nicholas Clark, Mason Crow, Shaw Yoshitani, Diana Thomas, Rob Lasater, Dusty Turner, and James Pleuss for their many great ideas to improve this material. We are very grateful to Joachim Gassen for developing the tidycovid19 package and allowing us to demonstrate some of its features here. In addition, we thank Nathan Tintle and Beth Chance for their assistance with our curriculum. Thank you to the associate editor and reviewers for their great suggestions for improving our work.

Supplementary Materials

The supplementary materials are available on GitHub at the following link: https://github.com/bryaneadams/Computational-Skills-for-Multivariable-Thinking-in-Introductory-Statistics.

Tidyverse tutorial:This tutorial is an intro course-friendly introduction to R and tidyverse we created for our course. Students learn to navigate RStudio, read in data files, use dplyr verbs to analyze data, and create visualizations with ggplot2. The dplyr verbs covered in the tutorial include summarize(), filter(), select(), mutate(), and group_by().

Classroom activities:We provide classroom activities used in our introductory course.

Course guide:Our course guide assists students with using technology to address the concepts in our course text.

ORCID

Kevin Cummiskey http://orcid.org/0000-0002-9537-3381