Using numbers to persuade?

David Kane writes,

I [Kane] am putting together a class on Rhetoric which will look the ways we use words, numbers and pictures to persuade. The class will have mininal prerequisites (maybe AP Stats or the equivalent) and will be discussion/tutorial based. For the sections on numbers and pictures, I plan on assigning “How To Lie with Statistics” by Huff and “The Visual Display of Quantitative Information” by Tufte. (The students will also be learning R so that they can produce some pretty pictures of their own. The course objectives are ambitious.)

Question: What other readings might people suggest? I am especially interested in readings that are either “classic” or freely available on the web.

I hope to teach the students are to attack and defend things like the IPCC report on global warming, the EPA report on secondhand smoke and so on.

Any suggestions would be much appreciated.

My response: I can’t actually think of any great examples, partly because once an issue seems clear, one way or another, persuasive reasoning seems almost a separate issue from quantitative reasoning. (I suppose this is parallel to the idea in science that if you do an experiment well, you don’t need statistics because the result will jump out at you.)

OK, I’ll give one recommendation: chapter 10 of my book on teaching statistics. Here are the table of contents and index for the book. I really like the index–I think it’s actually fun to read.

You ask for resources on the web. I suppose it won’t hurt to post one chapter . . . so here’s the aforementioned Chapter 10. (The images are clearer in the published book, but I think the pdf gives the general impression.) I hope you find it useful.

10 thoughts on “Using numbers to persuade?

  1. I recommend John Koomey's "Turning Numbers into Knowledge". Not freely available on the web, unfortunately, but worth the price.

    A site that specializes in critical analysis of numbers and statistics presented in the news media is http://www.stats.org/.

  2. I like Andrew's chapter. I also like the idea of case studies that illustrate how quantitative arguments have been misused, but I don't particularly like Huff's little book which hasn't aged well. On the (admittedly) few occasions that I've looked at stats.org, I've found their analyses to be shallow — they're "in-depth" analyses are usually short and (horrors!) graphics-free. If anything, they appear to fall under section 10.2.3 of Andrew's chapter.

    P.S. to David Kane: I (evidently) lean toward the broader meaning of "study replication."

  3. Not freely available, either, and I recommended it in a comment last week, but Statistics As Principled Argument, by Robert Abelson.

  4. "Inevitable Illusions" by Massimo Piattelli-Palmarini might be a good choice as well. It deals with common cognitive mistakes, particularly in the area of probability and statistics.

  5. For several years I taught a course on quantitative reasoning to non-science, non-math undergraduates. A particularly successful book in this course was the segment in which we read Stephen Jay Gould's The Mismeasure of Man, in which Gould lays out how quantitation was used to support the theories of phrenology and early "intelligence" testing. Interestingly, Gould unconsciously commits the same fundamental error in the second half of the book that he exposits in the first half. This makes the book a particularly useful teaching tool.

  6. "Inevitable Illusions" and "Mismeasure of Man" are both good suggestions. Another good one, perhaps a better match for your course as you have described it, is "A Mathematician Reads the Newspaper", by J.A. Paulos. It might also be worth taking a look at "200% of Nothing: An Eye Opening Tour Through the Twists and Turns of Math Abuse and Innumeracy" by A.K. Dewdney. (I have not read it, but just from the title it seems like it might be relevant.) Finally, Chance News tends to have lots of discussions of the sorts of things you're interested in. And it's free. Now that I think of it, I suspect you could teach a whole course using nothing but archived editions of Chance.

  7. Thanks to Andrew for posting my question and to all of the above for answering it. I will seek more comments and suggestions once I have a proper syllabus. In the meantime:

    1) I will use Andrew's chapter. Thanks!

    2) Mismeasure of Man is only a good book if you want to spend the time to debunk it. (Those interested can start here.) Alas, I probably won't have the time or energy for that exercise.

    3) I agree that the Abelson book is an informative read and that Chance News is great stuff.

    4) I am not sure what Robert Chung is referring to in his PS.

    5) Finally, I shouldn't bother our host, but I am confused by this statement.

    I can't actually think of any great examples, partly because once an issue seems clear, one way or another, persuasive reasoning seems almost a separate issue from quantitative reasoning.

    When do issues of public policy ever seem "clear"? Goodness knows that we all have our views of issues like global warming, public school vouchers, secondhand smoke, and the like — and there is a large amount of excellent research, statistical and otherwise, on them — but I don't believe that it is fair to claim that the views are settled or clear on any of them. Reasonable statisticians posterior probabilities differ, often dramatically.

    Does Andrew (or anyone) have a non-trivial example for which this is not the case?

  8. David,

    In answer to your question 5: I don't really know what I was saying there. I was trying to get at the notion that, although statistics are an important part of most policy arguments, the statistics by themselves never seem to resolve things.

    On a different point raised above: I read Inevitable Illusions several years ago and was disappointed. I mean, it was OK, but the edited book by Kahneman, Slovic, and Tversky from 1983 was much much more interesting.

    I also once read a stat textbook called Say it with Figures that was very disappointing. It looked really cool, but I looked into one of its examples (because it looked so cool, I wanted to go in depth for my class), and it turned out that the book had completely garbled the scientific article it was citing.

  9. Another book you might like to use as a reference is "Graphic Discovery – A Trout in the Milk and other Visual Adventures" by Howard Wainer.

    There is some overlap with Tufte's books, but I found it well written and interesting.

    For example, on page 72 – 77, there is an interesting display of how the ordering of data is can either expose or obscure structure. The example given that I liked was about the US Supreme Court.

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