Visualizing summary statistics and uncertainty

Authors:
K. Potter;J. Kniss;R. Riesenfeld;C. R. Johnson
Affiliations:
Scientific Computing and Imaging Institute, University of Utah;Department of Computer Science, University of New Mexico;School of Computing, University of Utah;Scientific Computing and Imaging Institute, University of Utah
Venue:
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
Year:
2010

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Abstract

The graphical depiction of uncertainty information is emerging as a problem of great importance. Scientific data sets are not considered complete without indications of error, accuracy, or levels of confidence. The visual portrayal of this information is a challenging task. This work takes inspiration from graphical data analysis to create visual representations that show not only the data value, but also important characteristics of the data including uncertainty. The canonical box plot is reexamined and a new hybrid summary plot is presented that incorporates a collection of descriptive statistics to highlight salient features of the data. Additionally, we present an extension of the summary plot to two dimensional distributions. Finally, a use-case of these new plots is presented, demonstrating their ability to present high-level overviews as well as detailed insight into the salient features of the underlying data distribution.