Year 2020, Volume 7 , Issue 2, Pages 255 - 265 2020-06-13

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

Fatih ORCAN [1]

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.
Normality test, Skewness, Mean comparison, Non-parametric tests
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Primary Language en
Subjects Education, Scientific Disciplines
Published Date June
Journal Section Articles

Orcid: 0000-0003-1727-0456
Author: Fatih ORCAN (Primary Author)
Institution: Trabzon Üniversitesi
Country: Turkey


Publication Date : June 13, 2020

APA Orcan, F . (2020). Parametric or Non-parametric: Skewness to Test Normality for Mean Comparison . International Journal of Assessment Tools in Education , 7 (2) , 255-265 . DOI: 10.21449/ijate.656077