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Comparisons of means were based on t tests after ensuring that the distributions being compared did not differ significantly from the normal distribution (Kolmogorov Smirnov tests) and did not differ significantly in their variances (Fisher's F tests).
The two groups which were compared did not exist at the same point in time.
More generally, the significance level of a predictor in the models compared did not necessarily attest to the amount of gain in prediction quality that might arise through the inclusion of this predictor.
The three groups, when compared, did not demonstrate any significantly different levels of VEGF gene expression.
Other study, in which CRP level was also compared, did not confirm this finding (Kritchevsky et al. 2000).
To rule out a bias attributable to patients discarded we compared each other groups, of all variables compared did not show differences.
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The number of valid bits compared does not follow this trend.
Although apparently simpler, the intersection between the images compared does not allow finding differences that could lead to improving the algorithms implemented in a CAD scheme.
However, CEA is less helpful if the treatments being compared do not affect the same health outcomes.
Unlike the F-test or the likelihood ratio test, the models being compared do not need to be nested [ 16].
Yet the "crisis presidents" to whom Mr. Obama is most appropriately compared don't have the luxury of serving bite-size initiatives.
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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