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The results of Levene's test showed that there are no significant differences (p > 0.05) in variances.
The Satterthwaite method was used when there was variability in variances.
Eventually, statistical differences between measured and predicted medians were evaluated using Mann-Whitney test, and differences in variances were evaluated using the Levene's test.
The idea behind uniform segmentation is that equally utilized each motion pixel and create a border based on their mean and change in variances.
Because of the heterogeneity in variances of the data, we applied a Kruskall-Wallis median comparison test (Dickens and Allen 2013).
Principal component 1 (PC1) accounted for the major differences in variances, whereas the principal component 2 (PC2) accounted for the minor differences.
For all analyses, Levene's test of homogeneity of variance was first performed to determine if there was significant difference in variances between groups.
After each iteration, the test of equality in variances is checked, and if the hypothesis is violated, the above mentioned method is applied.
A Levene's test on the absolute residuals of the cumulative leachate over 10 trials (ppb/cm2) indicated a significant difference in variances across pH (p = 1.42E-05) but not Brand (p = 0.176).
These results suggest that black catchup in raw grades can be virtually fully accounted for by differences in variances of grades across time as well as differences in grading practices across courses that blacks and whites take.
Given the shifts in variances' small sizes and disagreements in direction, the change in variance between the three models indicates that student performance on each assessment was equivalent whether administered as CBT or PPT.
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