A distribution-free test of analysis of variance hypotheses.

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Abstract
Rao''s technique of decomposing chi-square into components is modified to derive a distribution-free or nonparametric test of hypotheses involving main effects and interaction examined customarily by the analysis of variance of the two-factor or two-way variety. The proposed nonparametric test of analysis of variance hypotheses is described in terms of six principal steps, illustrated with a computational example, discussed with regard to small expected frequencies, compared with Mood''s tests which appear to be disadvantageous in treating interaction effects, and is possible to extend for designs of three or more factors.
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