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Statistical significance tests were performed with Chi-tests, Student's t-test or Mann-Whitney U-test depending on the scale level and distribution of normality.
Continuous variables were compared using the Student t or Mann–Whitney tests, and their correlation was tested using the Pearson or Spearman methods, according to their distribution of normality.
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Numerical variables showed a different distribution from normal standards (Gaussian distribution) (test of normality Shapiro-Wilk's, P > 0.05).
While making no assumption about the distribution of data, normality distribution testing of the continuous variables was performed using the non-parametric test; Kolmogorov-Smirnov test (KS-test).
The approximation of data distribution to normality was preliminarily tested.
The assumptions of binomial distribution and normality of errors were assessed by consideration of the standardised residuals.
Distribution normality of values for every studied population class was performed and checked with the Shapiro Wilk test.
Normal distribution of data was verified by normality plots.
Statistical analysis was performed in three stages: (1) Assessment of distribution and normality, (2) factor identification and (3) multivariate analysis.
The distribution and normality of data were assessed by visual inspection and using the Shapiro-Wilk test.
Testing of normality of distribution was performed with Q–Q plots.
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