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Kolmogorov-Smirnov tests were used to detect the normality distribution of the data.
The Kolmogorov-Smirnov test with Dallal-Wilkinson-Lillie for p value was used to assess the normality distribution of the data.
Following this transformation we controlled for the normality distribution assumption through the Shapiro-Wilks test.
The observation that experimental data obtained in L-CORT subjects meet the normality distribution assumption further supports this view.
The normality distribution was assessed using the Kolmogorov-Smirnov test.
The values of the total cohort were found to pass the normality distribution test.
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Initially we estimated Mardia's coefficients [ 58] to assess the multivariate normality distribution of the variables.
Kolmogorov Smirnov test was used to examine the data normality distribution.
Before performing the parametric tests, normality distribution of the data sets was tested by Kolmogorov Smimov and Shapiro Wilk tests.
A D'Agostino-Pearson test was conducted to test for normality distribution of the data.
Shapiro Wilk goodness-of-fit tests were used to assess the normality and distribution of data.
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