Visualization strives to present a comprehensive representation of information by displaying the data in a visual manner. An important aspect of comprehension is the understanding of error, confidence and other uncertainties present in the data or information. These additional characteristics of the information are often displayed as charts and graphs alongside the dataset, however it is often left out of visualizations. Techniques for visually representing the meaning of statistical descriptors including error, confidence and uncertainty can improve the effectiveness of visualizations used for data exploration and decision making.

• References
• PhD Proposal
• Proposal Slides
• Box Plot Survey
• Tech Report
• Vis '07 Phd Colloquim
• VACET Page
• Visualizing Large-Scale Uncertainty in Astrophysical Data Texture-Based Visualization of Uncertainty in Flow Fields


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