A quantile plot is a univariate plot in which the distribution of a measure is presented with pertinent statistical values, including quantiles, used as demarcations along the measure's scale. The individual measurements are presented in order from minimum to maximum along the other axis. This axis is divided into quantiles, typically quarters, and labeled with the fraction (between 0 and 1) which represents the applicable quantile. For example, the 0.5 quantile (which is the median) is the quantile for which half of the measurements are on the minimum side of the quantile line. The result is a pattern that represents the distribution of those measurements.

The following is an array of such plots. In a VisiCube array, you are presented individual plots for a single measure...each for a different set of records. An array gives you the ability to quickly compare the sets of records.

In this array comparing the heights of singers by voice part, you can easily see that height increases as the voice part decreases. It can also be seen that the high altos and high tenors have the greatest variation in height and that the latter are dispersed over that range quite evenly. Further, it appears that there are roughly the same number of singers for each voice part. But, because the spacing between points in a plot is dictated by the number of points, without counting you can see that there are fewer tenors than the other voice parts.

The data presented here is from a study of the heights of singers in the
New York Choral Society by J. M. Chambers, W. S. Cleveland, B. Kleiner, and P. A. Tukey.
It appeared in __Graphical Methods for Data Analyis__ which was
published in 1983 by __Chapman and Hall (New York).__

This data (and visual) is supplied with VisiCube as a sample project.