# How to Lie with Statistics

Darrell Huff

## Highlights

- proper treatment will cure a cold in seven days, but left to itself a cold will hang on for a week.
- The secret language of statistics, so appealing in a fact-minded culture, is employed to sensationalize, inflate, confuse, and oversimplify.
- It is sad truth that conclusions from such samples, biased or too small or both, lie behind much of what we read or think we know.
- 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 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?
- 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.
- The importance of using a small group is this: With a large group any difference produced by chance is likely to be a small one and unworthy of big type. A two-peracent-improvement claim is not going to sell much tooth-paste.
- Public pressure and hasty journalism often launch a treatment that is unproved, particularly when the demand is great and the statistical background hazy.
- 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, as when the Bureau of the Census tells you that there are nineteen chances out of twenty that their figures have a specified degree of precision. For most purposes nothing poorer than this five percent level of significance is good enough. For some the demanded level is one percent, which means that there are ninety-nine chances out of a hundred that an apparent difference, or whatnot, is real. Anything this likely is sometimes described as “practically certain.”
- Place little faith in an average or a graph or a trend when those important figures are missing.
- a difference is a difference only if it makes a difference.
- 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.
- Given a small sample, you are likely to find some substantial correlation between any pair of characteristics or events that you can think of.