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This article reviews the practical aspects of several nonparametric subset selection rules useful in block design problems, and discusses advantages and disadvantages of these methods. The populations are assumed stochastically ordered by the parameter of interest. Rules based on ranked observations are given for selecting a subset of populations which contains, with a specified confidence level, the population characterized by the smallest (or largest) parameter value. These procedures are applied to state traffic fatality rates recorded yearly (1960-76). New England states and Middle Atlantic states comprise most of the subset asserted, with a 90% confidence level, to contain the state with the smallest fatality rate; whereas, Southern states, Southwestern states and Rocky Mountain states generally comprise the subset for the state with the largest fatality rate. Note that while this example is not based on simulation data, such data would be analyzed in exactly the same fashion.

Nonparametric selection procedures applied to state traffic fatality rates