Explain why correlation alone is rarely sufficient to demonstrate cause.

Statistics
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Explain why correlation alone is rarely sufficient to demonstrate cause.

Jun 5th, 2015

Thank you for the opportunity to help you with your question!

here is a strong relationship between the number of ice cream cones sold and the number of people who drown each month.  Just because there is a relationship (strong correlation) does not mean that one caused the other.

If there is a relationship between A (ice cream cone sales) and B (drowning) it could be because

  • A->B (Eating ice cream causes drowning)
  • A<-B (Drowning cause people to eat ice cream-- perhaps the mourners are so upset that they buy ice cream cones to cheer themselves)
  • A<-C->B (Something else is related to both ice cream sales and the number of drowning-- warm weather would be a good guess)

The points is...just because there is a correlation, you CANNOT say that the one variable causes the other.  On the other hand, if there is NO correlations, you can say that one DID NOT cause the other (assuming the measures are valid and reliable).


Please let me know if you need any clarification. I'm always happy to answer your questions.
Jun 5th, 2015

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