When it comes to popularity rankings, correlational data can provide helpful perspective on ranking success.
The above statement is True.
With a correlational research design, correlations between two variables—or more—are examined without any of the variables being under the researcher's direct control or manipulation. It is a form of quantitative study that is not experimental.
The link between height and weight is a good example. Taller persons typically weigh more. When there is a negative correlation between two variables, it means that when one variable rises, the other one falls.
Correlational study, for instance, may show the statistical link between high income earners and relocation; that is, the likelihood that someone will relocate or not increases with money.
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