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Accordingly, the assumptions of normal distribution and homogeneity of variances were met.
Data were statistically analyzed by analysis of variance (ANOVA) and Duncan test (α = 0.05), when the assumptions of normal distribution and homogeneity of variances were met.
If assumptions of normal distribution and equality of variances could not be assured, a nonparametric Friedman test was undertaken instead (Statview, SAS, Cary, NC, USA).
Although our sample size is relatively large (n = 124), our data did not meet the assumptions of normal distribution and equal measurement intervals; we therefore chose to use a nonparametric test (Wilcoxon matched-pairs signed-ranks test) to establish whether differences between pretest and post-test scores were statistically significant.
This method is based on multidimensional scaling of complex data sets in order to determine relationships with no assumptions of normal distribution.
The procedure relaxes the assumptions of normal distribution and identity link [35], a crucial prerequisite for the ordinal data of this study.
Similar(41)
Assumptions of normal distributions were tested by histograms and QQ-plots.
This result indicated that the raw data were not systematically deviating from assumptions of normal distributions.
The Kolmogorov-Smirnov test was used to confirm assumptions of normal distributions.
To be analyzed with the GLM, signals must satisfy the assumption of normal distribution [32]; however, the actual responses of regional cerebral blood flow (rCBF) are not necessarily normally distributed.
Under the assumption of normal distribution, each eigenvalue can be described by its expectation and variance.
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