Brushing Moments in Interactive Visual Analysis

We present a systematic study of opportunities for the interactive visual analysis of multi-dimensional scientific data that is based on the integration of statistical aggregations along selected independent data dimensions in a framework of coordinated multiple views (with linking and brushing). Traditional and robust estimates of the four statistical moments (mean, variance, skewness, and kurtosis) as well as measures of outlyingness are integrated in an iterative visual analysis process. Brushing particular statistics, the analyst can investigate data characteristics such as trends and outliers. We present a categorization of beneficial combinations of attributes in 2D scatterplots: (a) kth vs. (k + 1)th statistical moment of a traditional or robust estimate, (b) traditional vs. robust version of the same moment, (c) two different robust estimates of the same moment. We propose selected view transformations to iteratively construct this multitude of informative views as well as to ...

• Type: Journal
• Year: 2010
• Where: CGF
• Authors: Johannes Kehrer, Peter Filzmoser, Helwig Hauser
• Keywords: CGF 2010, Robust Estimates, Statistical Moment, Visual Analysis