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WHY CORRELATION DOES NOT IMPLY CAUSATION?

Seema Singh

Aug 24, 2018·4 min read



Correlation and causation are terms which are mostly misunderstood and often
used interchangeably. Understanding both the statistical terms is very important
not only to make conclusions but more importantly, making correct conclusion at
the end. In this blogpost we will understand why correlation does not imply
causation.



A lot of times we have heard “correlation does not cause causation” or
“correlation does not imply causation” or “correlation is not causation”. But
what they mean actually by saying this?

You will get a clear idea once we go through this blogpost. So let’s start!


GETTING THE BASICS RIGHT

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.

Correlation does not mean causality or in our example, ice cream is not causing
the death of people.



When 2 unrelated things tied together, so these can be either bound by causality
or correlation.

In Majority of the cases correlation, are just because of the coincidences. Just
because it seems like one factor is influencing the other, it doesn’t mean that
it’s actually does.

Correlation is something which we think, when we can’t see under the covers. So
the less the information we have the more we are forced to observe correlations.
Similarly the more information we have the more transparent things will become
and the more we will be able to see the actual casual relationships.


Relationship of sunny days with ice-cream sales and homicide


CONSIDER UNDERLYING FACTORS BEFORE CONCLUSION

In some cases there are some hidden factors which are related on some level.
Like in our example of ice cream sales and homicide rates , weather is the
hidden factor which is causing both the things.Weather is actually causing the
rise in ice cream sales and homicides. As in summer people usually go out, enjoy
nice sunny day and chill themselves with ice creams. So when it’s sunny, wide
range of people are outside and there is a wider selection of victims for
predators.



There is no causal relationship between the ice cream and rate of homicide,
sunny weather is bringing both the factors together. And yes, ice cream sales
and homicide has a causal relationship with weather.


DON’T CONCLUDE TOO FAST!

Just after finding correlation, don’t draw the conclusion too quickly. Take time
to find other underlying factors as correlation is just the first step. Find the
hidden factors, verify if they are correct and then conclude.

Hope this post cleared your doubts!

Thanks for reading!!


SEEMA SINGH

Data Science Aspirant| Learner

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