Wednesday 3 September 2008

Cause and effect

I have often wondered how people (whether they be members of the public, statisticians or scientists) decide on cause and effect.
For example
Whenever ice cream sales rise, so do shark attacks.
As more economists are recruited to the Treasury, inflation rises.
Are shark attacks caused by people eating more ice cream? maybe there is some chemical compound released from the skin after consumption of ice cream which causes a shark to go into a frenzy and attack the consumer or is it more likely that more ice cream is consumed at the same time as more people go in the sea (i.e. summer) and it is the increased numbers off people in the sea which causes an increase in shark attacks?

The lesson: This is a foolish case of a simple error - the assumption that things happening after an event must be caused by it.

Everyone examines data for evidence that their side is right. If a statistical morsel seems to our taste, the temptation is to swallow it. 

Such zeal produces, in this case, the following logic:

Here's event A - a smoking ban.
Here's event B - a selective fall in heart attacks.
Therefore, A caused B.

Sometimes the numbers go up, sometimes down. If you simply take the period, or the place, in which the numbers go the way you want, but disregard the rest, you are likely to read meaning into nothing.

This is one problem with arguments about causality, the belief that any change must have a principal cause, when it may be the result of the many causes that produce nothing more meaningful than random variation.

The key is not to stop looking for the cause with the first plausible link you find. Keep your imagination restless for other causes, or the possibility of chance, and it will serve you well.


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