The phrase "relationship of variables" is correct and usable in written English.
It can be used in contexts such as statistics, mathematics, or research when discussing how different variables interact or influence each other.
Example: "The study aimed to explore the relationship of variables such as income and education level."
Alternatives: "interaction of variables" or "correlation between variables."
One-way ANOVA, Pearson product moment correlation, and Spearman rank correlation coefficient analyses were performed in SPSS ver.16.0 to examine the variation and relationship of variables.
To further understanding of the factors influencing adolescents' motivations for physical activity, the relationship of variables derived from Self-Determination Theory to adolescents' affective response to exercise was examined.
In this study, MI is employed in that MI is a flexible nonparametric tool and can measure the relationship of variables with arbitrary distributions.
However, some of equations of nonlinear form make the relationship of variables difficult to determine.
Pearson correlation test was performed to evaluate the relationship of variables.
We also identified the nonmonotonical relationship of variables if the range of changing pattern of effect could be determined.
Concretely, artificial neural network (ANN) is utilized as the basic structure capturing nonlinear relationships of variables.
Use of SEM is recommended as it uses both factor analysis and multiple regressions to find out interrelated relationships of variables (Hair et al. 2006).
Such intelligent learning methods use kernel function as the basis, which could extend the linear algorithms to the nonlinear relationships of variables.
To observe the relationships of variables between tests, Spearman rank correlation was used because in most cases the data did not meet the assumptions of normality (Shapiro-Wilk test p<0.05) despite data transformation.
Quantitative data from the questionnaires were analysed quantitatively to explain relationships of variables and for comparability purposes.
