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Activity Number: 587 - Recent Advances in Statistical Graphics
Type: Contributed
Date/Time: Wednesday, August 2, 2017 : 2:00 PM to 3:50 PM
Sponsor: Section on Statistical Graphics
Abstract #323218 View Presentation
Title: A Bayesian Approach to Visual Inference
Author(s): Susan VanderPlas* and Heike Hofmann and Eric Hare
Companies: and Iowa State University and Iowa State University
Keywords: Visualization ; Statistics ; Graphics ; Perception ; Bayesian

Graphics play a crucial role in statistical analysis and data mining. The lineup protocol for experimentally testing graphics has traditionally used p-values to identify plots which are significantly visually distinct from distractor plots, but this approach does not easily translate to examining randomly generated plots to determine the strength of the distractor effect. This study presents a Bayesian approach to visual inference, using bayes factors to examine the difference in signal strength in two-target statistical lineups.

Authors who are presenting talks have a * after their name.

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