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Statistical distances quantifies the difference between two statisticalconstructs. In this article, we describe reference values for a distancebetween samples derived from the Kolmogorov-Smirnov statistic $D_{F,F'}$. Eachmeasure of the $D_{F,F'}$ is a measure of difference between two samples. Thisdistance is normalized by the number of observations in each sample to yieldthe $c'=D_{F,F'}\sqrt{\frac{n n'}{n+n'}}$ statistic, for which high levelsfavor the rejection of the null hypothesis (that the samples are drawn from thesame distribution). One great feature of $c'$ is that it inherits therobustness of $D_{F,F'}$ and is thus suitable for use in settings where theunderlying distributions are not known. Benchmarks are obtained by comparingsamples derived from standard distributions. The supplied example applicationsof the $c'$ statistic for the distinction of samples in real data enablesfurther insights about the robustness and power of such statistical distance.

A Statistical Distance Derived From The Kolmogorov-Smirnov Test: specification, reference measures (benchmarks) and example uses