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# Correlation vs. Causation: Why do we care about the difference?

Many statistics students have likely heard their instructor say the phrase, "correlation does not mean causation."  As a statistics student, you may have even recited this phrase during a discussion or included the phrase in a written assignment.  But what does this phrase truly mean and why do we care?

Consider this scenario:

A researcher wants to examine the impact that watching the show "The Jersey Shore" has on an IQ test performance for a class of Introductory Statistics students. To investigate the relationship, the instructor surveys the classroom and asks students to 1) answer some questions that will be used to calculate their IQ and 2) indicate the amount of time (in hours per week) they spend watching The Jersey Shore. The instructor compares the responses for hours spent watching The Jersey Shore to student performance on the IQ test and finds a strong, negative relationship, r(30) = -.45. Remember, a strong negative relationship here means that as the number of hours spent watching The Jersey Shore increases, IQ scores decrease.

"A-ha!" the instructor exclaims. "This is why you should not watch that horrible television show. Watching The Jersey Shore is causing your intelligence to decrease!"

Is this instructor correct? Should the government put a stop to airing this horrible television show? Do these results demonstrate that watching The Jersey Score causes lower intelligence scores, in essence making people less intelligent?