By Adam Loy, Carleton College
In introductory statistics, we traditionally visualize inferential concepts related to inference using static graphics or interactive apps. For example, there is a long history of using apps to visualize sampling distributions. Recent developments in statistical graphics have created an opportunity to bring additional visualizations into the classroom to hone student understanding. Specifically, the lineup protocol (Buja et al., 2009) provides a framework for students see the difference between signal and noise. This protocol involves embedding a plot of observed data in field of “noise plots.” This approach has proved valuable in visualizing randomization/permutation tests, diagnosing models, and even conducting valid inference when distributional assumptions break down (Loy, Follett & Hofmann, 2016; Loy, Hofmann & Cook, 2017). This poster will provide an overview of the lineup protocol for visual inference and how we use it in our statistics courses, most notably the first and second courses in statistics.