It is important not to assume causality from a correlation because correlation only shows that two variables are related, not that one causes the other. ...
It is important not to assume causality from a correlation because correlation only shows that two variables are related, not that one causes the other. There may be other factors (called third variables) that influence both. If we assume causation too quickly, we may draw wrong conclusions.
A simple example of a spurious correlation is the relationship between ice cream sales and drowning rates. They often increase at the same time, but ice cream does not cause drowning. The real reason is hot weather, which increases both.
In my correlation matrix, the relationship between study time and GPA (r = .62) could be mistaken as cause-effect. It might seem that studying more directly causes higher GPA. However, this is not always true because other factors like motivation, intelligence, or study methods may also affect GPA. Therefore, we cannot say study time alone causes better academic performance.