![]() ![]() The graph shows that the region that has the highest density is near (x,y) = (125, 225). Title2 "Individual Observations Are Not Shown" For convenience, the Systolic variable is renamed X and the Cholesterol variable is renamed Y: The data are measurements of the systolic blood pressure (the "top number") and cholesterol levels of 5,057 patients in a heart study. The following SAS DATA step extracts data from the Sashelp.Heart data set and will be used to create all graphs. Use color to visualize the density of points. Use a scatter plot to show the markers.Use transparency to visualize the density of points. Use a contour map to visualize the density.The individual markers are not shown, but outliers are visible. Use a heat map to visualize the density.This article shows the following four methods of visualizing the density of bivariate data: These plots do a good job communicating density, but they typically do not show individual points, which can be a drawback if you are interested in displaying outliers. You can overcome that problem by moving from a "point plot" to an "area plot" such as a heat map or a contour plot. Scatter plots (indeed, all plots that show individual markers) can suffer from overplotting, which means that the graph does not indicate how many observations are at a specific ( x, y) location. In a scatter plot that displays many points, it can be important to visualize the density of the points. ![]()
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