CORRELATION VS. CAUSATION The Logic of Social Science

One of the most important rules of social sciences is the axiom, “Correlation does not mean Causation”.

Correlation: 1. A mutual relationship of any two or more things. 2. Statistics: an interdependence between random variables or between sets of numbers. Example: There is a correlation between climate and vegetation

Causation: 1. Whatever produces and effect. 2. The relation of cause and effect. Example: The flood caused much damage.

If my dog howls at the moon, particularly when it is “blue”, then what can be assumed? Causation: 1. The moon causes my dog to howl (Correct) 2. My dog’s howling turns the moon blue (Incorrect) Correlation: 1. There is a correlation between the blue moon and my dog’s increased howling patterns.

Determining causation is the biggest problem for a social scientists. Clearly, it is easy to make mistakes and misinterpret data. Data is also sometimes tampered with or used selectively by some people to support false conclusions.