Research Article

Empirical Type 1 Error Rate and Power Comparisons of Normality Tests with R

Volume: 39 Number: 3 September 30, 2018
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Empirical Type 1 Error Rate and Power Comparisons of Normality Tests with R

Abstract

Normality is one of the main presuppositions in statistical tests. The multiplicity of the normality tests bring out another problem of choosing the appropriate test for researchers. The free software R which has a great popularity in the statistical analysis has 18 normality tests in 4 different packages. In this study we compared performance of these normality tests in terms of empirical type 1 error rate and power by Monte Carlo simulation. As a result, regardless of the distribution of data (symetric or asymmetric) the Shapiro-Francia test, also the Frosini B test performed better than the other normality tests in terms of experimental type 1 error rate. However the widely used Kolmogorov-Smirnov test showed worse performance than other normality tests in terms of empirical type 1 error rate and power.

Keywords

References

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Details

Primary Language

English

Subjects

-

Journal Section

Research Article

Authors

Aydın Karakoca
0000-0001-6503-3872
Türkiye

Publication Date

September 30, 2018

Submission Date

May 23, 2018

Acceptance Date

September 3, 2018

Published in Issue

Year 1970 Volume: 39 Number: 3

APA
Pekgör, A., Erişoğlu, M., Karakoca, A., & Erişoğlu, Ü. (2018). Empirical Type 1 Error Rate and Power Comparisons of Normality Tests with R. Cumhuriyet Science Journal, 39(3), 799-811. https://doi.org/10.17776/csj.426382

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