Scagnostics

Scagnostics (scatterplot diagnostics) refers to a series of measures that characterize certain properties of a point cloud in a scatter plot. The term and idea was coined by John Tukey and Paul Tukey, though they didn't publish it; later it was elaborated by Wilkinson, Anand, and Grossman. The following nine dimensions are considered:[1][2]

  1. For the outliers in the data:
    1. outlying
  2. For the density of data points:
    1. skewed
    2. clumpy
    3. sparse
    4. striated
  3. For the shape of the point cloud:
    1. convex
    2. skinny
    3. stringy
  4. For trends in the data:
    1. monotony
Scatterplot matrix of the scagnostics measures for the 91 scatterplots of the variables of the Boston Housing data set

References
  1. Wilkinson, Leland (23 April 2008). "Scagnostics". Retrieved 25 March 2022. {{cite journal}}: Cite journal requires |journal= (help)
  2. Wilkinson, Leland; Anand, Anushka; Grossman, Robert (2005). "Graph-theoretic scagnostics". In Proc. 2005 IEEE Symp. On Information Visualization (INFOVIS: 157–164. CiteSeerX 10.1.1.329.1315.
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