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    Empirical Type 1 Error Rate and Power Comparisons of Normality Tests with R
    (2018) Pekgör, Ahmet; Erişoğlu, Murat; Karakoca, Aydın; Erişoğlu, Ülkü
    Normality is one of the main presuppositions instatistical tests. The multiplicity of the normality tests bring out anotherproblem of choosing the appropriate test for researchers. The free software Rwhich has a great popularity in the statistical analysis has 18 normality testsin 4 different packages. In this study we compared performance of thesenormality tests in terms of empirical type 1 error rate and power by MonteCarlo simulation. As a result, regardless of the distribution of data (symetricor asymmetric) the Shapiro-Francia test, also the Frosini B test performedbetter than the other normality tests in terms of experimental type 1 errorrate. However the widely used Kolmogorov-Smirnov test showed worse performancethan other normality tests in terms of empirical type 1 error rate and power.