Presented by:Shonda Kuiper, Ying Long, Zachary Segall & Krit Petrachai, Grinnell College
AbstractThrough interactive visualization tools, we provide several examples of activities that focus on core statistical issues that are often challenging to teach with traditional textbooks, such as working with messy data, data relevance and reliability. We have created lab activities for introductory and advanced courses that search for patterns within the stop-and-frisk data sets for New York City, which allow police to stop and question any individual they find suspicious. In recent years, the New York Police Department had been under fire for allegedly discriminating against certain races. These materials challenge students to think carefully about collecting data, cleaning data, appropriate model building, assessment, and effectively communicating their results.
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