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Above: 5 students, each having marks in 4 courses, listed in the data table at bottom center. One student is highligted in red, another in blue. Above left: a scatterplot matrix, or SPLOM. Above right: parallel coordinates.

Above: techniques for visualizing multidimensional multivariate (mdmv) data. "Multidimensional" refers to there being multiple independent variables in the data, and "multivariate" refers to there being multiple dependent variables. If there is 1 independent variable and 1 dependent variable (1 i.v. + 1 d.v.), we can use a bar chart or line chart to visualize the data. 0 i.v. + 2 d.v.: a scatterplot. 2 i.v. + 1 d.v.: a table of numbers, table of bars, or heatmap. Many i.v.: recursively subdivided axes, as in Polaris and Tableau software. Many d.v.: glyphs (such as Chernoff faces), scatterplot matrix (SPLOM), or parallel coordinates.

The above figure is published and explained in my 2012 article Simple Algorithms for Network Visualization: A Tutorial.