A cluster analysis computer program is presented which uses the K-Means algorithm to obtain partitions of multivariate data which have low within-class variance. The program provides a somewhat novel form of a next-nearest neighbor analysis, convenient cross tabulations for variables other than the ones used in the clustering, an efficient form of variable clustering, and approximate randomization tests for a variety of relationships.
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