Abstract
Scagnostics is a Tukey neologism for the term scatterplot diagnostics. Scagnostics are characterizations of the 2D distributions of orthogonal pairwise projections of a set of points in multidimensional Euclidean space. These characterizations include such measures as density, skewness, shape, outliers, and texture. We introduce a set of scagnostics measures based on graph theory and we analyze their distributions and performance. Our analysis is based on a restrictive set of criteria that must be met in order to have scagnostics measures that can be used effectively in exploratory data analysis.
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