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Hypotheses were then confirmed through ANOVA, mean comparison, and multi-regression analysis.
They used mean comparison and item response theory to examine participant performance at both the assessment and item levels.
Mean comparison and the subsequent stepwise multiple regression were applied to find superior features from different color spaces.
Mean comparison and multiple analysis of variance (MANOVA) reveal that bitumen grade significantly affects CSS, whilst content and ageing of RAP would have insignificant effect on CSS.
The effect of level of C. palmensis on nutritive properties of diets was assessed by analysis of variance followed by mean comparison and regression analysis.
The one-sample t test was used for dependent variable mean comparison, and one-way analysis of variance (ANOVA) test and its nonparametric equivalent, the Kruskal Wallis test, were used for variables that were small and not normally distributed.
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Correlational analyses, group mean comparisons, and discriminant function analyses were conducted to examine the validity of the CHEDS.
Computations Tukey post-hoc means comparisons and Levene's test for equal variance was also included.
Computations Tukey post-hoc means comparisons and Levene's test for equal variance was also used to assess the difference between group means.
Results were subjected to analysis of variance and mean comparison by Tukey test, and to simple linear and canonical correlations by SAS.
The results were submitted to statistical analysis by outlier tests, normality test, homogeneity variance, analysis of variance and mean comparison, all with 95%% reliability.
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