Correctional studies examine the relationships between variables in a study. Positive relationships (positive correlations) exist when high scores on one variable are associated with high scores on another variable, as when intelligence is positively correlated with grade point average. Inverse relationships (negative correlations) exist when high scores on one variable are associated with low scores on a second variable, as when the amount of sleep one gets is negatively correlated with levels of irritability and anxiety.
Demonstrating that a correlation exists does not show that changes in one variable are the cause of changes in the other, partly because other factors which are undetected may be influencing both known variables. For example, it is possible that a third variable is causing a change in both variables measured, or that a third variable is causing a change in just one of the two variables. Simply put, there are a number of possibilities. Thus, knowing that a correlation exits may lead to two or more different interpretations of the correlation. For the studies described below, decide whether the correlation is positive or negative and give three explanations for the finding. Here is an example:
A study found that the more an elderly person exercised, the more gray matter was found in fMRI scans.
Type of correlation: Positive
One explanation: The amount of gray matter in one’s brain increases one’s propensity to exercise.
Another explanation: Exercise increases gray matter
A third explanation: People who are likely to have large amounts of gray matter as they age are also likely to lead healthy lifestyles that include exercise, eating right, and maintaining healthy relationships.
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