For example, the effectiveness measure was nonnegative, but the model was based on normality assumptions, thus predictive effectiveness values can be negative.
It is worthy to note that this measurement is a powerful tool for dealing with fuzzy phenomena and is based on normality, monotonicity, self-duality, and maximality axioms.
The Wan et al. estimator of the standard deviation is based on normality assumption and uses approximation of expected values of the order statistics.
P-values and confidence intervals given by the NLMIXED procedure are based on asymptotic normality which may not be accurate for small sample sizes.
Tests and interval estimates for the model parameters are based on the approximate normality of the maximum likelihood estimators.
The Wald confidence intervals shown in Table 3 are based on the asymptotic normality of the parameter estimators.
Biological criteria of normality are based on statistical concepts.
First, for many statistically less well trained users it is hard to verify to which extent statistical procedures for comparing means are based on theoretical assumptions such as normality or homoscedasticity, i.e. homogeneous or equal variances among all groups.
The probability values (p-values) for differences between groups are based on the assumptions of the normality of the distribution of spot intensities and equal variances.
An additional consideration is that the contours on the funnels are constructed assuming normality of the effect size since they are based on the Wald test.
