In statistics, the Cucconi test is a nonparametric test for jointly comparing central tendency and variability (detecting location and scale changes) in two samples.
Many rank tests have been proposed for the two-sample location-scale problem.
First, from a historical point of view, it was proposed some years before the Lepage test, the standard rank test for the two-sample location-scale problem.
Thirdly, it compares favorably with Lepage type tests in terms of power and type-one error probability[2] and very importantly it is easier to be computed because it requires only the ranks of one sample in the combined sample, whereas the other tests also require scores of various types as well as to permutationally estimate mean and variance of test statistics because their analytic formulae are not available.
The interest on this test has recently increased spanning applications in many different fields like hydrology, applied psychology and industrial quality control.