[Colloquium] Fwd: FRIDAY, 10:30am | Visualizing Uncertainty

[Sandra Wallace via Colloquium]

> ---------- Forwarded message ---------
> From: Mark Sorkin <msorkin at uchicago.edu <mailto:msorkin at uchicago.edu>>
> Date: Wed, Nov 28, 2018 at 11:00 AM
> Subject: FRIDAY, 10:30am | Visualizing Uncertainty
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> The Neubauer Collegium for Culture and Society 
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> View this email in your browser <https://mailchi.mp/uchicago/hullman_113018?e=da793e6ce1> 
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>  <https://uchicago.us15.list-manage.com/track/click?u=41468719d37c56fff66b526a9&id=132c5b2780&e=da793e6ce1>
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> Visualizing Uncertainty
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> Supporting Reasoning about Uncertainty with Data Visualization
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> November 30, 2018
> 10:30 a.m. – 12:00 p.m.
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> Neubauer Collegium
> 5701 S. Woodlawn Ave.
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> Charts, graphs, and other visualizations amplify cognition by enabling users to visually perceive trends and differences in quantitative data. While guidelines dictate how to choose visual encodings and metaphors to support accurate perception, it is less obvious how to design visualizations that encourage rational decisions and inference. At this lecture, sponsored by the VUE Project <https://uchicago.us15.list-manage.com/track/click?u=41468719d37c56fff66b526a9&id=223f0dd4c1&e=da793e6ce1> at the Neubauer Collegium, Jessica Hullman <https://uchicago.us15.list-manage.com/track/click?u=41468719d37c56fff66b526a9&id=34fc7fe2b4&e=da793e6ce1> (Assistant Professor in Computer Science and Journalism, Northwestern University) will address two challenges that must be overcome to support effective reasoning with visualizations. First, people’s intuitions about uncertainty often conflict with statistical definitions. Hullman will describe research in her lab that shows how visualization techniques for conveying uncertainty through discrete samples can improve non-experts’ ability to understand and make decisions from distributional information. Second, people often bring prior beliefs and expectations about data-driven phenomena to their interactions with data that influence their interpretations. Most design and evaluation techniques do not account for these influences. Hullman will describe what her research team has learned by developing and studying visualization interfaces that encourage reflecting on data in light of one’s own or others’ prior knowledge. She will conclude by reflecting on how better representations of uncertainty and prior knowledge can contribute to improved thinking and decision making with visualizations as well as deeper understanding around the interpretation process.
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