Exact(18)
Levine's test was used to check the assumption of equal sample variances, and the Kolmogorov-Smirnov test along with visual examination of normal probability plots was used to verify data normality for all ANOVA analyses.
D'Agostino-Pearson testing demonstrated normality for all variables under study (p > 0.1).
The Kolmogorov Smirnov test was used to assess the assumption of normality for all datasets evaluated.
Excessive kurtosis would also explain the reasoning for high Jarque-Bera statistics, which reject the null hypothesis of normality for all return series.
Normality for all data was confirmed by the Komogorov Smirnov test for equality.
Kolmogorov-Smirnov Goodness of Fit Tests showed normality for all outcome measures.
Similar(42)
Additionally, plots of sorted residuals versus theoretical quantiles of the normal distribution revealed evidence of non-normality for all four exposures.
Normal quantile plots of the residuals were used to examine the normality assumption for all linear models.
That normality lasted for all of four seconds.
In order to choose the appropriate statistical tests, we contrasted the normality hypothesis for all the pairs of samples with the Shapiro Wilk and the Kolmogorov-Smirnov tests.
Normality assumption for all continuous variables was tested using the Shapiro-Wilk test.
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