Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison

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International Journal of Assessment Tools in Education
Volume:7 Issue:2
Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison

Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison

Pages : 255-265

View : 101 | Download : 10

Publication Date : 2020-06-13

Article Type : Research Paper

Abstract :Checking the normality assumption is necessary to decide whether a parametric or non-parametric test needs to be used. Different ways are suggested in literature to use for checking normality. Skewness and kurtosis values are one of them. However, there is no consensus which values indicated a normal distribution. Therefore, the effects of different criteria in terms of skewness values were simulated in this study. Specifically, the results of t-test and U-test are compared under different skewness values. The results showed that t-test and U-test give different results when the data showed skewness. Based on the results, using skewness values alone to decide about normality of a dataset may not be enough. Therefore, the use of non-parametric tests might be inevitable.
Keywords : Normality test, Skewness, Mean comparison, Non parametric

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