How to Lie with Statistics

When you are told that something is an average you still don’t know very much about it unless you can find out which of the common kinds of average it is—mean, median, or mode.

So when you see an average-pay figure, first ask: Average of what? Who’s included?

The fact is that, despite its mathematical base, statistics is as much an art as it is a science. A great many manipulations and even distortions are possible within the bounds of propriety.

If the source of your information gives you also the degree of significance, you’ll have a better idea of where you stand. This degree of significance is most simply expressed as a probability,

What’s Missing?

In the end it was found that if you wanted to know what certain people read it was no use asking them. You could learn a good deal more by going to their houses and saying you wanted to buy old magazines and what could be had?

The point is that when there are many reasonable explanations you are hardly entitled to pick one that suits your taste and insist on it. But many people do.

To be worth much, a report based on sampling must use a representative sample, which is one from which every source of bias has been removed.

The fallacy is an ancient one that, however, has a powerful tendency to crop up in statistical material, where it is disguised by a welter of impressive figures. It is the one that says that if B follows A, then A has caused B.