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Comparison was performed with an analysis of variance using the Tukey post-hoc test.
Data obtained were subjected to analysis of variance using the general linear models.
Data were subjected to a one-way analysis of variance using the least significant difference method.
We accomplished this using log-linear regression by which we estimated the variance using the negative binomial distribution.
Averages and standard deviations were submitted to analysis of variance using the Tukey test with a 5% level of significance.
In Factor 1 (Dangerous Violations), we can account for 25.5 % of the variance using the predictors under scrutiny.
All data were subjected to analysis of variance using the general linear models procedure (SAS Institute, Cary, NC).
In addition, most nonlinear design approaches involve assuming normality of the posterior distribution and approximate its variance using the expected Fisher information matrix.
Prior to conducting statistical analyses, all data were checked for normality and homogeneity of variance using the Kolmogorov-Smirnov and Levene's test.
The results were analyzed for variance using the SAS/STAT statistical analysis package (version 6.12; SAS Institute, Cary, NC, USA) to determine significant differences.
Prior to model training, all descriptors were centered to have zero mean and scaled to have unit variance using the function PreProcess.
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