Red Light Reaction – A Statistics Project with Real Life Application

We describe a hands-on project in which students collect data on the impact of distracted driving on driver reaction time. Initially they do this in class via a virtual driving applet, using themselves and fellow students as test subjects. Different applet versions simulate driving with and without distraction and measure the time it takes to apply brakes after the red brake lights of the car ahead appear. Students use the collected data to practice a range of statistical techniques, such as assessing data for outliers, creating a hypothesis to be tested, performing an appropriate test, and then translating their results to determine a safe driving distance. In the second part of the project, students work in groups outside of class. Each group recruits a category of test subjects (e.g., athletes, video gamers, STEM majors) of their choosing, collects data, and performs statistical analysis. Finally, students develop hypotheses as to whether different categories of drivers have better or worse reaction times, collect additional relevant data, and perform the appropriate statistical test. The applets, the project guide, the dataset, and supporting videos can be downloaded from https://osf.io/h8yxw/files/osfstorage. For users of the Canvas LMS, we also provide an export cartridge that contains the various project components. Supplementary materials for this article are available online.

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Publication Details

Journal
Journal of Statistics and Data Science Education
Published
2024-09-23
DOI
https://doi.org/10.1080/26939169.2024.2407781
Citations
1
Primary Topic
Statistics Education and Methodologies
Type
article
Field-Weighted Citation Impact
0.71
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article

Red Light Reaction – A Statistics Project with Real Life Application

Silvia Heubach, Tuyetdong Phan-Yamada
1 citations
Journal of Statistics and Data Science Education
Statistics Education and Methodologies
0.71
article

Red Light Reaction – A Statistics Project with Real Life Application

Silvia Heubach, Tuyetdong Phan-Yamada
article en
1 citations

Abstract

We describe a hands-on project in which students collect data on the impact of distracted driving on driver reaction time. Initially they do this in class via a virtual driving applet, using themselves and fellow students as test subjects. Different applet versions simulate driving with and without distraction and measure the time it takes to apply brakes after the red brake lights of the car ahead appear. Students use the collected data to practice a range of statistical techniques, such as assessing data for outliers, creating a hypothesis to be tested, performing an appropriate test, and then translating their results to determine a safe driving distance. In the second part of the project, students work in groups outside of class. Each group recruits a category of test subjects (e.g., athletes, video gamers, STEM majors) of their choosing, collects data, and performs statistical analysis. Finally, students develop hypotheses as to whether different categories of drivers have better or worse reaction times, collect additional relevant data, and perform the appropriate statistical test. The applets, the project guide, the dataset, and supporting videos can be downloaded from https://osf.io/h8yxw/files/osfstorage. For users of the Canvas LMS, we also provide an export cartridge that contains the various project components. Supplementary materials for this article are available online.

Journal of Statistics and Data Science EducationVol. 33(1)
California State University Los Angeles (US)
Openalex Percentile: Top 26%
Statistics Education and Methodologies
0.71
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