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The distribution's normality (checked using the Shapiro Wilk test); Mean, standard deviation, median, mode, range, interquartile range, standard error of the mean (SEM), coefficient of variation (CV, or relative standard deviation RSD); The summary box plots of the variables (on standardized values).
The natural logarithmic transformed AhR-mediated activities and markers of POPs improved the normality (checked by Q-Q plots) and homogeneity of variance, and the statistical analysis was performed on the ln-transformed data.
Natural logarithmic transformation of AhR-TEQ/AhRcomp and POP data improved the normality (checked by Q-Q plots) and homogeneity of variance, and the statistical analysis was performed on the ln-transformed data.
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Data normality was checked by normal probability plots, Kolmogorov Smirnov test and coefficients of skewness and kurtosis.
Univariate normality checking showed histogram and Q-Q plot of 36 items were normally distributed.
MFMR conducted data collection, data cleaning and normality check.
Mean and standard deviations (SDs) were estimated for all continuous variables, after normality checks.
Diagnostic checks were undertaken to ensure adherence to all model assumptions, including outlier tests and normality checks on the residuals.
The data normality was checked with the Shapiro test for normality.
Normality as checked by histograms and Kolmogorov-Smirnov tests for normal distribution was not given for most variables.
Normality was checked by visual inspection of quantile plots.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com