A test is proposed for deciding whether one of k populations has slipped to the right of the rest, under the null hypothesis that all populations are continuous and identical. The procedure is to pick the sample with the largest observation, and to count the number of observations r in it which exceed all observations of all other samples. If all samples are of the same size n, n large, the probability of getting r or more such observations, when the null hypothesis is true, is about k1−r.
Some remarks are made about kinds of errors in testing hypotheses.
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Mosteller, F. (2006). A k-Sample Slippage Test for an Extreme Population. In: Fienberg, S.E., Hoaglin, D.C. (eds) Selected Papers of Frederick Mosteller. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-44956-2_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-0-387-20271-6
Online ISBN: 978-0-387-44956-2