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:
“It is known that Whistler when asked how long it took him to paint one of his “nocturnes” answered: “All of my life.” With the same rigor he could have said that all of the centuries that preceded the moment when he painted were necessary. From that correct application of the law of causality it follows that the slightest event presupposes the inconceivable universe and, conversely, that the universe needs even the slightest of events.”
—Jorge Luis Borges (1899–1986)