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Give an example (state the identity of two variable) where a silly, false (i.e. nonsense) high correlation value might be discovered and identify a more appropriate variable to replace one of the two variables.

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We must use common sense when we analyze data and discover correlation exists. A large value for a correlation coefficient does not necessarily mean that real correlation exists. One of the classic examples is the study that discovered a high correlation between the increased use of illegal drugs by high school students and the increased number of high school teachers. What more relevant factors could have caused this classic case of nonsense correlation, and why?

Give a similar example (state the identity of two variables) where a silly, false (i.e., nonsense) high correlation value might be discovered and identify a more appropriate variable to replace one of the two variables.

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The solution discusses correlation values and their interpretations in the context of high school students and teachers.

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Give an example (state the identity of two variable) where a silly, false (i.e. nonsense) high correlation value might be discovered and identify a more appropriate variable to replace one of the two variables.

This problem is concerned with what is known as a spurious correlation. A spurious correlation occurs when two variables are correlated, yet have no causal relationship. This event can happen because of the effects of a third variable, sometimes called a "lurking variable" or ...

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