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The variance of knowledge levels among agents is maximal in the small world region, whereas the coefficient of variation is minimal.
Analysis of variance (ANOVA) was done to identify socio-demographic variance of knowledge score on warning signs and risk factors of colorectal cancer.
Socio-demographic variance of knowledge score on warning signs and risk factors were identified by ANOVA and presented in (Table 4).
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Overall, the variables in Model 5 explained approximately 27.5% of variance of the knowledge score.
Furthermore, there was a considerable amount of variance in knowledge of dementia which cannot be explained by either the demographic characteristics or experience caring for, or learning specifically about caring for, people with dementia.
Only gender (p<0.001) and education (p<0.001) moderated the relationship between samples (2007 and 2013) and knowledge, accounting for 38% of the variance in knowledge of guidelines.
Design knowledge intensity and throughput variance are both aspects of knowledge, the former relating to organizational management knowledge and the latter characteristic of operational process knowledge.
The amount of variance in knowledge examination scores phase 1 accounted for by predictors (adjusted R) was 22.0% and decreased to 19.3% by phase 3 (see Table 3).
Overall, the binary logit regression model explained about 70.6% of the variance of local people's knowledge on the adverse impacts of Eucalyptus woodlot (Table 5).
On the other hand, the binary logit regression model explained about 70.6% of the variance of local people's knowledge on the adverse impacts of Eucalyptus woodlot.
The overall multivariate logistic regression model was statistically significant (LR χ(7) = 35.61; p < 0.001) and it accounted for 15.9% of the variance in perceived knowledge of medical errors definition (Pseudo R2 = 15.88).
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CEO of Professional Science Editing for Scientists @ prosciediting.com