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The phrase "relationships between variables" is grammatically correct and can be used in written English.
It refers to the connections and interactions between different factors or elements in a situation or experiment. Example: In order to understand the impact of exercise on mental health, researchers studied the relationships between variables such as frequency of exercise, type of exercise, and self-reported levels of anxiety and depression.
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The relationships between variables underwent linear regression analysis method.
A correlation coefficient was calculated to test relationships between variables.
Dependency modelling - the establishment of relationships between variables.
Possible relationships between variables were evaluated by linear regression.
Pearson's correlation analysis was conducted to test relationships between variables.
Causal relationships between variables could not be confirmed.
To examine the relationships between variables we used methods of correlation and regression analysis.
In such visualizations we show the important pair-wise relationships between variables.
Therefore, research questions are open and researchers avoid hypotheses predicting relationships between variables.
Regression models provide a powerful tool for investigation of relationships between variables.
The use of PCA clarifies the relationships between variables and phenomenon behind these correlations (Fig. 2a).
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linkages between variables
ratios between variables
connections between variables
relationships between variations
relationships between characteristics
relationships between values
relationships between attributes
relationships between measures
relationships between varieties
relationships between years
interactions between variables
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relationships between variance
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