Chance News 18
How to Lie with Statistics Turns Fifty.
A review of "How to Lie with Statistics Turns Fifty"
Media Highlights, The College Mathematics Journal, Vol. 37, No 3, May 2006
Norton Starr
The College Mathematics Journal (CMJ) Media Highlights covers mathematics generally and its reviews often involve probability or statistical concepts, so Chance News readers would enjoy these reviews. As with this review, the probability and statistical contributions are usually written by Norton Starr who has been a great help to Chance News.
Here Norton reviews a special section of Statistical Science, August 2005 that recognized the 50th birthday of Darrell Huff’s famous book "How to Lie with Statistics" by asking several authors to contribute the articles for this birthday party. These articles are:
"Darrell Huff and Fifty Years of How to Lie with Statistics", Michael Steele.
"Lies, Calculations and Constructions: Beyond How to Lie with Statistics", Joel Best.
"Lying with Maps", Mark Monmonier.
"How to Confuse with Statistics or: The Use and Misuse of Conditional Probabilities", Walter Krämer and Gerd Gigerenzer.
"How to Lie with Bad Data", Richard D. De Veaux and David J. Hand.
"How to Accuse the Other Guy of Lying with Statistics", Charles Murray.
"Ephedra", Sally C. Morton.
"In Search of the Magic Lasso: The Truth About the Polygraph", Stephen, E. Fienberg and Paul C. Stern.
Norton gives a nice description of each of the papers but we (Laurie Snell) will restrict ourselves to some quotes from the articles that we found particularly interesting.
Michael Steeles tells us the story of the life of Darrell Huff and begins with:
In 1954 former Better Homes and Gardens editor
and active freelance writer Darrell Huff published a slim (142 page) volume, which over time would become the most widely read statistics book in the history of the world.
There is some irony to the world’s most famous statistics book having been written by a person with no formal training in statistics, but there is also some logic to how this came to be. Huff had a thorough training for excellence in communication, and he had an exceptionalcommitment to doing things for himself.
In his article Joel Best reminds us of the failure of the "critical thinking" movement in the late 1980's and the 1990's and asks "who would teach it”. He is not very optimistic about this being done in statistics courses or in social science courses. And we were not very successful in getting people to teach our Chance course. He concludes his article with:
We all know statistical literacy is an important problem,
but we’re not going to be able to agree on its place in the curriculum. Which means that "How to Lie with Statistics" is going
to continue to be needed in the years ahead.
When we read the "The Bell Curve" by Richard Herrnstein and Charles Murray to review for Chance News, it seemed to us that the reviewers in the major newspapers could not have actually read the book. So we wrote a long review of the book for Chance News (Chance News 3.15, 3.16, 4.01).
In his article Charles Murray explains six ways to knock down a book. He discribes these as:
Tough but effective strategies for making people think that the target book is an irredeemable mess, the findings are meaningless, the author is incompetent and devious and the book’s thesis is something it isn’t.
Our experience with "The Bell Curve" made us realize that we may have seen an example of his Method 6 which he calls "THE BIG LIE" and describes as follows:
THE JUDICIOUS USE OF THE BIG LIE.
Finally, let us turn from strategies based on halftruths and misdirection to a more ambitious approach: to borrow from Goebbels, the Big Lie. The necessary and sufficient condition for a successful Big Lie is that the target book has at some point discussed a politically sensitive issue involving gender, race, class or the environment, and has treated this issue as a scientifically legitimate subject of investigation (note that the discussion need not be a long one, nor is it required that the target book takes a strong position, nor need the topic be relevant to the book’s main argument). Once this condition is met, you can restate the book’s position on this topic in a way that most people will find repugnant (e.g., women are inferior to men, blacks are inferior to whites, we don’t need to worry about the environment), and then claim that this repugnant position is what the book is about.
What makes the Big Lie so powerful is the multiplier effect you can get from the media. A television news show or a syndicated columnist is unlikely to repeat a technical criticism of the book, but a nicely framed Big Lie can be newsworthy. And remember: It’s not just the public who won’t read the target book. Hardly anybody in the media will read it either. If you can get your accusation into one important outlet, you can start a chain reaction. Others will repeat your accusation, soon it will become the conventional wisdom, and no one will remember who started it. Done right, the Big Lie can forever after define the target book in the publicmind.
Finally I agree with Norton's final remark in his review:
The articles are both a compliment to and a complement of Huff's pathbreaking venture in writing. This issue of Statistical Science is destined to be a collector's item.
Submitted by Laurie Snell