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Original Articles

Robustness to Non-Normality of Common Tests for the Many-Sample Location Problem

Pages 187-206 | Published online: 15 Jun 2010
 

Abstract

This paper studies the e(r)ect of deviating from the normal distribution assumption when considering the power of two many-sample location test procedures: ANOVA (parametric) and Kruskal-Wallis (non-parametric). Power functions for these tests under various conditions are produced using simulation, where the simulated data are produced using MacGillivray and Cannon's [10] recently suggested g-and-k distribution. This distribution can provide data with selected amounts of skewness and kurtosis by varying two nearly independent parameters.

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