Visualizing Summary Statistics and Uncertainty

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dc.contributor.authorPotter, Kristinen_US
dc.contributor.authorKniss, Joeen_US
dc.contributor.authorRiesenfeld, Richarden_US
dc.contributor.authorJohnson, Chris R.en_US
dc.contributor.editorG. Melancon, T. Munzner, and D. Weiskopfen_US
dc.date.accessioned2014-02-21T20:05:49Z
dc.date.available2014-02-21T20:05:49Z
dc.date.issued2010en_US
dc.description.abstractThe 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.en_US
dc.description.number3en_US
dc.description.seriesinformationComputer Graphics Forumen_US
dc.description.volume29en_US
dc.identifier.doi10.1111/j.1467-8659.2009.01677.xen_US
dc.identifier.issn1467-8659en_US
dc.identifier.urihttps://doi.org/10.1111/j.1467-8659.2009.01677.xen_US
dc.publisherThe Eurographics Association and Blackwell Publishing Ltd.en_US
dc.titleVisualizing Summary Statistics and Uncertaintyen_US
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29-Issue 3
EuroVis10: Eurographics/ IEEE Symposium on Visualization