Comparing the performance of modified Ft statistic with

Abstract: ANOVA is a classical test statistics for testing the equality of groups. However this test is very sensitive to nonnormality as well as variance heterogeneity. To overcome the problem of nonnormality, robust method such as Ft test statistic can be used but the test statistic can only perform well when the assumption of homoscedasticity is met. This is due to the biasness of mean as a central tendency measure. This study proposed a robust procedure known as modified Ft method which combines the Ft statistics with one of the popular robust scale estimators, MADn, Tn and LMSn. A simulation study was conducted to compare the robustness (Type I error) of the method with respect to its counterpart from the parametric and non parametric aspects, ANOVA and Kruskal Wallis respectively. This innovation enhances the ability of modified Ft statistic to provide good control of Type I error rates. The findings were in favor of the modified Ft method especially for skewed data. The performance of the method was demonstrated on real education dat