Seminars archive
Upcoming Seminars   Colloquium Title to be announced Sherry Li, Lawrence Berkeley National Lab  Past Seminars   Seminar: Computer Science Humancentered Data Science for Crisis Informatics Marina Kogan, University of Colorado   Seminar TBD TBD,   Seminar: Algebra Congruence of Galois representations Sujatha Ramdorai, University of British Columbia   Defense: Dissertation Extremal Problems for Graphs and Hypergraphs Bill Kay, Emory University   Seminar: Computer Science Designing Abstract Meaning Representations Martha Palmer, University of Colorado   Seminar A Method for Landscape Exploration in Global Optimization. Manuela Manetta, Emory University   Seminar Curvature through Cubes Michael Carr, Emory University   Computer Science Bias and Uncertainty in Information Visualization Michael Correll, University of Washington Venue: Mathematics and Science Center, Room W303 Show abstract We often turn to data to help us make sense of an uncertain world. However, the uncertainty in our data is often esoteric, complex, or counterintuitive. It can be challenging to present this uncertainty, especially to audiences without backgrounds in statistics.
Charts, graphs, and other visualizations of data address this issue by making people into “visual statisticians:” we can estimate statistical properties through visual inspection. However, just as statistical measures can be subject to bias, visualizations can also introduce bias.
In this talk, I show how designers can intervene to create new visualizations that correct these biases, and improve the judgments of visual statisticians. From this perspective of designing for debiasing, I focus on two common visualizations: error bars and thematic maps. I present visual alternatives for error bars that avoid “withinthebar” bias while also promoting statistically grounded comparisons between means. I also present “Surprise Maps,” a technique for thematic maps that relies on Bayesian reasoning to highlight interesting regions that might otherwise be hidden in traditional maps. I conclude with a discussion of remaining challenges for visual debiasing, and how we might use visualizations to encourage better, datadriven decisionmaking.   Seminar: Algebra The Distribution Of The Number Of Prime Factors With Restrictions  Variations Of The Classical Theme Krishna Alladi, University of Florida   Seminar: Combinatorics Bounded colorings of graphs and hypergraphs Jan Volec, McGill University 
