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All Times EDT

Friday, June 5
Data Visualization
User Testing Statistical Graphics
Fri, Jun 5, 3:30 PM - 5:05 PM
TBD
 

Expect Users to Satisfice: Designing Interfaces for Reasoning with Uncertainty (308079)

Jessica Hullman, Northwestern University 
*Alex Kale, University of Washington 

With the proliferation of data-driven products and media in public life, conventional statistical graphics tend to emphasize point estimates and omit uncertainty information. However, given that research in visualization, psychology, and behavioral economics shows that people often satisfice (i.e., use heuristics that deviate from the optimal strategy) when reasoning with uncertainty, users of data visualizations may not recognize or correctly interpret uncertainty. I argue that we need to understand users’ potential reasoning strategies in order to design graphical interfaces that steer users toward more systematic ways of reasoning with uncertainty. In this talk, I present empirical evidence on how users satisfice, both when reading individual charts and when conducting analysis, and I discuss ways we are designing statistical graphics and interfaces for data analysis that anticipate users’ tendency to satisfice.