Question

Why cant correlations be used as a tool to prove a causal relationship between variables, rather than just an association?

Answer 1

To get the casual relationship means that to calculate the causation.
So the question is basically asking that why correlation can't be used to measure causation.

Let's dig a little deeper into this.

Correlation is a statistical technique which tells us how strongly the pair of variables are linearly related and change together. It does not tell us why and how behind the relationship but it just says the relationship exists.

Example: Correlation between Ice cream sales and sunglasses sold.
As the sales of ice creams is increasing so do the sales of sunglasses.

Causation takes a step further than correlation. It says any change in the value of one variable will cause a change in the value of another variable, which means one variable makes other to happen. It is also referred as cause and effect.
Example: When a person is exercising then the amount of calories burning goes up every minute. Former is causing latter to happen.

So now we know what correlation and causation is, it’s time to understand “Correlation does not imply causation!” with a famous example.

Ice cream sales is correlated with homicides in New York (Study)

As the sales of ice cream rise and fall, so do the number of homicides. Does the consumption of ice cream causing the death of the people?

No. Two things are correlated doesn’t mean one causes other. Hence, correlation may be misleading when used as a tool to prove casual relationship between variables.

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