Bringing Visual Inference to the Classroom

TL;DR

This paper explores how the lineup protocol for visual inference can enhance statistical education by providing intuitive visualizations that help students distinguish signal from noise and understand key concepts.

Contribution

It introduces the application of the lineup protocol as a teaching tool across various statistical topics in the curriculum.

Findings

Lineup protocol improves student understanding of statistical inference.

Visualizations help diagnose models and conduct valid inference.

The approach integrates seamlessly into existing curricula.

Abstract

In the classroom, we traditionally visualize inferential concepts 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 for visual inference provides a framework for students see the difference between signal and noise by embedding a plot of observed data in a field of null (noise) plots. Lineups have proven valuable in visualizing randomization/permutation tests, diagnosing models, and even conducting valid inference when distributional assumptions break down. This paper provides an overview of how the lineup protocol for visual inference can be used to hone understanding of key statistical topics throughout the statistics curricula.