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