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A basic cross-tabulation analysis is widely used in this paper to analyze the correlation between variables and to expose the differences between age groups and gender.
Correlation between variables was determined using Spearman's correlation test.
Correlation between variables was measured using Spearman's ρ.
Fig. 4 Correlation between variables and principal components.
The results of Pearson correlation between variables are summarized in Table 5.
The correlation between variables of principal factor 3 suggests the following results.
Absence of an arrow indicates a lack of correlation between variables.
Correlation between variables was studied by Pearson Moment test.
Pearson's correlation coefficient (r) was calculated to examine the correlation between variables.
Correlation between variables was assessed by Spearman rank test or regression analysis.
Bivariate correlation between variables was tested with Pearson's correlation.
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