Sentence examples for deviation from the normality from inspiring English sources
Ordinary least squares regression requires that model residuals have a normal distribution, while our walking behavior data are skewed to the left with a great deviation from the normality assumption.
Referred to any part, partition and bars susceptible to harm the animals; the teguments of animals were also checked to detect any sign of deviation from the normality.
Although the F-test is simple and is widely used to quantify differences in variance, it is sensitive to deviation from the normality assumption or presence of outliers (e.g. unexpectedly higher or lower expression values from one or two samples).
This deviation from the normality assumption by phenotypes can render many QTL mapping approaches inappropriate, in senses of less accuracy and effectiveness in QTL detection (Coppieters et al., 1998), and unstable results due to outliers (Pinheiro et al., 2001).
The functions in Limma have considerable good toleration to mild or moderation deviation from the normality assumption and moderated t-test is the most commonly used method to identify DEGs.
The simulation results suggest that the proposed Bayesian approach is not sensitive to mild or moderate deviations from the normality assumption for the expression intensities.
The Kolmogorov-Smirnov test was used, and histograms and Q-Q plots were examined to verify if there were significant deviations from the normality assumption of continuous variables.
The Shapiro-Wilk test was used, and histograms and normal quantile plots were examined to verify whether there were significant deviations from the normality assumption of continuous variables.
Since there were no significant deviations from the normality assumption, the general linear model (GLM) was performed using a multivariate approach for left and right side measurements separately for the blocks of dependent variables.
The results show that the proposed model is useful when the gene coverage is widely different among component studies in the meta-analysis, which agrees with the observation in Simulation I. We examine the robustness of the proposed method to deviations from the normality assumption in (1) for gene expression intensities and compare its performance with MAPEs when this assumption is not satisfied.
