Sentence examples for deviation of normality from inspiring English sources

Furthermore, the methods used in analyzing twin data are robust to minor deviation of normality.

Stratified bootstrapping method was used for stratified ethnicity and for multiple testing bias corrections due to deviation of normality.

MANCOVA test with 1,000 stratified bootstrap samples, and bias corrected and accelerated (BCa) 95% CI was used for multiple testing bias corrections due to deviation of normality.

ANCOVA test was used, followed by pairwise comparison using 1,000 stratified bootstrap samples with bias corrected and accelerated (BCa) 95% CI for multiple testing bias corrections due to deviation of normality.

Deviations of normality were slight and most pronounced in the symptom scales.

Because we did not find extreme values or outliers in these descriptives and because of the large size of this study we can interpret that our method seems fairly robust against the deviations of normality that exist in kurtosis.

Although, rank based correlation methods, such as the Spearman correlation, have been used to reduce the prevalence of spurious correlations due to deviations from assumptions of normality in expression data, we have observed in practice that the Spearman correlation coefficient performs similarly to the Pearson when comparing with MMC (data not shown).

Further, the results might be also affected even Bollen-Stine bootstrap was used to manage the effect of deviation form normality, so the usage of polychoric correlations would be an alternative.

Due to a general deviation from the requirements of normality of most variables, non-parametric univariate statistics (Mann-Whitney, Kruskal-Wallis) were used for univariate analyses, and Classification Tree for multivariate analyses.

Furthermore, it is shown that the predictions are quite sensitive to the value of the maximum angle of deviation from normality in the non-normality flow rule.

The performance of multilayer perceptron (MLP) and that of linear regression (LR) were compared, with regard to the quality of prediction and estimation and the robustness to deviations from underlying assumptions of normality, homoscedasticity and independence of errors.