How to Lie with Statistics

The test of the random sample is this: Does every name or thing in the whole group have an equal chance to be in the sample? The purely random sample is the only kind that can be examined with entire confidence by means of statistical theory, but there is one thing wrong with it. It is so difficult and expensive to obtain for many uses that sheer c

So it is with much that you read and hear. Averages and relationships and trends and graphs are not always what they seem. There may be more in them than meets the eye, and there may be a good deal less. The secret language of statistics, so appealing in a fact-minded culture, is employed to sensationalize, inflate, confuse, and oversimplify. Stati

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.

What’s Missing?

comparisons between figures with small differences are meaningless. You must always keep that plus-or-minus in mind, even (or especially) when it is not stated.

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

To say “almost one and one-half” and to be heard as “three”—that’s what the one-dimensional picture can accomplish.

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.

It is the illusion of the shifting base that accounts for the trickiness of adding discounts. When a hardware jobber offers “50% and 20% off list,” he doesn’t mean a seventy percent discount. The cut is sixty percent since the twenty percent is figured on the smaller base left after taking off fifty percent.