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Describe an example in which two variables are strongly correlated, but changes in one does not...

Describe an example in which two variables are strongly correlated, but changes in one does not cause changes in the other. Does correlation imply causation?

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Answer #1

Example in which two variables are strongly correlated, but changes in one does not cause changes in the other.

Variable 1: Ice cream Sales

Variable 2: Sunglasses sold

We note that Ice cream Sales and Sunglasses sold are strongly positively correlated. As the Ice cream Sales goes up, correspondingly Sunglasses sold also goes up. But, Sunglasses sold is not the cause of Ice cream Sales. Correlation does not imply correlation. Correlation just tells us how the 2 variables: Variable 1: Ice cream Sales and Variable 2: Sunglasses sold are linearly related. Causation says any change in the value of one variable causes change in the value of the other variable. The correlation between Ice cream Sales and Sunglasses sold is due to the presence of the Confounding Variable: Temperature. Since it very hot, both ice cream as well as sun glasses are sold more.

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