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Exploring a complex gender wage gap dataset: an introductory activity in identifying issues and data visualization
Authors:Robert S. Lasater  Anny-Claude Joseph  Kevin Cummiskey
Affiliation:Mathematical Sciences, United States Military Academy, New York, USA
Abstract:In this paper, we provide instructors with an approach for a classroom activity for students in an introductory data science or statistics course who have little or no statistical programming experience. We designed this activity to help students improve their statistical literacy while exploring a social justice problem-the gender wage gap. To minimize the challenges of developing statistical literacy in students who lack programming skills, we developed a web-based data visualization application that does not require users to have any prior programming knowledge. The data in this visualization application comes from the March 2018 Current Population Uniform Extracts detailed by the Center for Economic Policy Research. Students can use the visualization application to create tables and plots to explore data on factors such as earnings and gender. Instructors can also use the application for other wage-related variables, such as race, occupation and family size.
Keywords:teaching  data analysis  social justice  statistics
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