Datalab FacultyJessica Hullman
Many people, including analysts, find uncertainty and probability difficult to reason about when working with data. The use of null hypothesis significance testing is increasingly criticized, however we lack good representations of uncertainty that can provide analysts and readers of scientific literature with “cognitive evidence” for understanding variation, reliability, and related statistical concepts.
This project has focused on developing a method for visualizing uncertainty more concretely as a set of possible outcomes. By watching possible outcomes “play out” in an animated or interactive format, the user gains a better sense of which data patterns are reliable and which are not. The approach generalizes to a number of data inputs and complex visualization types that lack uncertainty representations.
- Hypothetical Outcome Plots Outperform Error Bars and Violin Plots
- blog post on Hypothetical Outcome Plots.
- The Visual Uncertainty Experience
- When(ish) is my Bus? User Centered Visualizations of Uncertainty
- Evaluating Approaches to Crowdsourced Visual Analytics
- Why Evaluating Uncertainty Visualization is Error Prone