# How to Lie with Statistics, by Huff

Monday April 5, 2021

Darrell Huff and his popular 1954 book have received criticism. Huff was wrong about cigarettes and cancer, but he did warn us that people are biased. In 142 breezy pages, the book manages to cover quite a lot, with perhaps moderate levels of prejudice for its time.

• Chapter 1: “The Sample with the Built-in Bias” (sampling)
• Chapter 2: “The Well-Chosen Average” (mean vs. median)
• Chapter 3: “The Little Figures That Are Not There” (variance etc.)
• Chapter 4: “Much Ado about Practically Nothing” (small differences and measurement uncertainty)
• Chapter 5: “The Gee-Whiz Graph” (funny y-axes)
• Chapter 6: “The One-Dimensional Picture” (dimensional distortion of comparisons)
• Chapter 7: “The Semiattached Figure” (non-sequitur logic)
• Chapter 8: “Post Hoc Rides Again” (correlation ≠ causation)
• Chapter 9: “How to Statistculate” (“statistically manipulate”—nonsense math)
• Chapter 10: “How to Talk Back to a Statistic” (ask questions)
• “Who says so?”
• “How does he know?”
• “What’s missing?”
• “Did somebody change the subject?”
• “Does it make sense?”

"There are at least three levels of sampling involved. Dr. Kinsey's samples of the population (one level) are far from random ones and may not be particularly representative, but they are enormous samples by comparison with anything done in his field before and his figures must be accepted as revealing and important if not necessarily on the nose. It is possibly more important to remember that any questionnaire is only a sample (another level) of the possible questions and that the answer the lady gives is no more than a sample (third level) of her attitudes and experiences on each question." (page 23)

"Some of the strongest feeling against public-opinion polls is found in liberal or left-wing circles, where it is rather commonly believed that polls are generally rigged. Behind this view is the fact that poll results so often fail to square with the opinions and desires of those whose thinking is not in the conservative direction. Polls, they point out, seem to elect Republicans even when voters shortly thereafter do otherwise." (page 26)

Interesting historical perspective; modern concerns about polls are not necessarily new issues.

"You will also learn if you read back into the tables that the figure is based on a sample of such size that there are nineteen chances out of twenty that the estimate—\$3,107 before it was rounded—is correct within a margin of \$59 plus or minus." (pages 35-36)

I don’t know a confidence interval technique that will give you quite that interpretation; this could be erroneous.

"Degree of significance" (p-value) is presented on page 42 as a thing that is usually hidden from the public, which may have been (and may still often be) the case. These days I hear more about problems with significance tests than demands for them.

"It is dangerous to mention any subject having high emotional content without hastily saying where you are for or agin it." (page 46, amusing spelling in original)

"The Procrustean Statistic" (graphic page 43)

"In somewhat the same fashion those little figures [reporting variance] that are missing from what are called “Gessell’s norms” have produced pain in papas and mamas. Let a parent read, as many have done in such places as Sunday rotogravure sections, that “a child” learns to sit erect at the age of so many months and he thinks at once of his own child. Let his child fail to sit by the specified age and the parent must conclude that his offspring is “retarded” or “subnormal” or something equally invidious. Since half the children are bound to fail to sit by the time mentioned, a good many parents are made unhappy. Of course, speaking mathematically, this happiness is balanced by the joy of the other fifty per cent of parents in discovering that their children are “advanced.” But harm can come of the efforts of the unhappy parents to force their children to conform to the norms and thus be backward no longer." (pages 44-45)

"Newsweek once showed how “U. S. Old Folks Grow Older” by means of a chart on which appeared two male figures, one representing the 68.2-year life expectancy of today, the other the 34-year life expectancy of 1879-1889.'"

Here Huff is complaining that the person twice as tall appears 8 times as massive, but there are other issues with interpreting historical life expectancy...

"Who knows what germ causes colds, particularly since it probably isn’t a germ at all?" (page 75)

What does he think causes colds? They knew about viruses in the 50s, didn’t they?

"Let us say that during a period in which race prejudice is growing you are employed to “prove” otherwise. It is not a difficult assignment. Set up a poll or, better yet, have the polling done for you by an organization of good reputation. Ask that usual cross section of the population if they think blacks have as good a chance as white people to get jobs. Repeat your polling at intervals so that you will have a trend to report.

"Princeton’s Office of Public Opinion Research tested this question once. What turned up is interesting that things, especially in opinion polls, are not always what they seem. Each person who was asked the question about jobs was also asked some questions designed to discover if he was strongly prejudiced against blacks. It turned out that people most strongly prejudiced were most likely to answer Yes to the question about job opportunities. (It worked out that about two-thirds of those who were sympathetic toward blacks did not think the black had as good a chance at a job as a white person did, and about two-thirds of those showing prejudice said that blacks were getting as good breaks as whites.) It was pretty evident that from this poll you would learn very little about employment conditions for blacks, although you might learn some interesting things about a man’s racial attitudes." (pages 75-76)

A couple striking dehumanizing "blacks" vs. "white people" phrasings here. The reportage of veiled (?) racism in survey responses still seems relevant today.

"A civilian population includes infants, the old, and the ill, all of whom have a higher death rate wherever they are." (page 85)

It’s incidental to the point of the text here, but it’s interesting to see a reference to infants having a high death rate. I think this sounds out of place, today. When Huff was born in 1913, something like ten percent of babies died before age five. (historical life expectancy)

"Keep in mind that a correlation may be real and based on real cause and effect—and still be almost worthless in determining action in any single case." (page 93)

"But arbitrarily rejecting statistical methods makes no sense either. That is like refusing to read because writers sometimes use words to hide facts and relationships rather than to reveal them." (page 121)

"I’ll face up to the serious purpose that I like to think lurks just beneath the surface of this book: explaining how to look a phony statistic in the eye and face it down; and no less important, how to recognize sound and usable data in that wilderness of fraud to which the previous chapters have been largely devoted." (page 122)

"You may be familiar with the Rudolf Flesch readability formula. It purports to measure how easy a piece of prose is to read, by such simple and objective items as length of words and sentences. Like all devices for reducing the imponderable to a number and substituting arithmetic for judgment, it is an appealing idea." (page 137)

I’m interested in the readability stuff, but it also strikes me that the last sentence there is quite a good joke:

"Like all devices for reducing the imponderable to a number and substituting arithmetic for judgment, it is an appealing idea."

That could be an epigraph!