Correlation and Causality
When two variables are related, or correlated, one can make predictions for these two variables . However, it is important to note that this does not mean causality. At this point, it is not possible to determine a causal relationship between the two variables; correlation does not imply causality. However, correlation evidence is significant because it can help identify potential causes of behavior. Path analysis is a statistical technique that can be used with correlational data. This involves the identification of mediator and moderator variables. A mediator variable is used to explain the correlation between two variables. A moderator variable affects the direction or strength of the correlation between two variables. A spurious relationship is a relationship in which the relation between two variables can be explained by a third variable.
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Famous quotes containing the word causality:
“Any important disease whose causality is murky, and for which treatment is ineffectual, tends to be awash in significance.”
—Susan Sontag (b. 1933)