I was lucky enough to be a T.A. for Fred Mosteller in his final year of teaching introductory statistics at Harvard. He had taught for 30 years and told us that in different years he emphasized different material–he never knew what aspect of the course they would learn the most from, so each year he focused on what interested him the most.
Anyway, every week he would take his three T.A.’s to lunch to talk about how the course was going and just to get us talking about things. One day he asked us what we thought about some issue of education policy–I don’t remember what it was, but I remember that we each gave our opinions. Fred then told us that, as statisticians, people are interested in our statistical expertise, not in our opinions. So in a professional context we should be giving answers about sampling, measurement, experimentation, data analysis, and so forth–not our off-the-cuff policy opinion, which are not what people were coming to us for.
I was thinking of this after reading David Kane’s comment on Sam’s link to an article about the book, The Bell Curve. David asked me (or Sam) to tell us what we really think about the Bell Curve. I can’t speak for Sam, but I wouldn’t venture to give an opinion considering that I haven’t read the book. I’d like to think I’m qualified to make judgments about it, if I were to spend the effort to follow all the arguments–but it would take a lot of time, and my impression is that a bunch of scientists have already done so (and have come to various conclusions on the topic). I would imagine that I might be inclined to study the issue further if I were involved in a study evaluating educational policies, for example, but it hasn’t really come up in any of my own research. (I did think that James Flynn’s article on a related topic was interesting, but I don’t even really know what are the key points of The Bell Curve are, so I wouldn’t presume to comment.
Over the years, I’ve been distressed to see statistians and other academic researchers quoted as “experts” in the news media, even for subjects way out of their areas of expertise. It takes work to become an expert on a topic. Teaching classes in probability and statistics isn’t always enough. As a reaction to this, I’ve several times said no to media requests on things that I’m not an expert on. (For example, when asked to go on TV to comment on something on the state lottery, I forwarded them to Clotfelter and Cook, two economists at Duke who wrote an excellent book on the topic.) Standards for blogs are lower than for TV, but still . . .
A reasonable opinion, well expressed. I wouldn't have asked for your opinion on The Bell Curve if I hadn't (stupidly) mistaken you as the author of the previous post.
You write: "[M]y impression is that a bunch of scientists have already done so [commented on The Bell Curve] (and have come to various conclusions on the topic)." Which scientists and/or which commentary? Those of us who have read The Bell Curve are always on the look-out for informed commentary by smart people. Your suggestions would be most welcome.
AG: As a reaction to this, I've several times said no to media requests on things that I'm not an expert on.
But you also chose not to comment on the question of whether Don Rubin's statistical analyses for the tobacco industry were biased. This question is well within your area of expertise.So isn't a more parsimonious hypothesis that you just prefer not to take stands on controversial issues, regardless of whether they are in your area of expertise or not?
Regarding educational policy, there appears to be room within introductory courses to explore peoples' instinctive biases that are inconsistent with statistical reasoning. Examples include base rate neglect, loss aversion, and overfitting. Andrew has touched on some of these issues here before, and some of the examples from the "bag of tricks" book home in on these problems. Developing a curriculum with input from psychologists would seem to serve students really well.
A very respectable position. On the one hand, you certainly have the right to express your opinion on any subject that strikes your fancy. Lack of expertise is never an obstacle: pick up any newspaper, or read (almost) any blog. On the other hand, because of your reputation in the area of statistics, there would be a tendency for the public at large to value your opinion on any subject more highly than they would value the opinion of a random man on the street. You, in other words, start off with a much more favorable prior!
David,
I've actually read nothing on The Bell Curve except for book reviews when it came out. But I recall that some CMU statisticians wrote an evaluation of it several years ago; this is what I was thinking of.
Deb,
I have not read Rubin's statistical analysis for the tobacco industry. Based on everything else I've seen by him, and given that causal inference is one of his central research areas, I strongly expect that I'd agree with the technical aspects of his findings if I were to put in the effort to read and evaluate them.
Chris,
I love these topics, although I have to admit that undergraduates aren't so fascinated by these experiments. My current thinking on intro stat is to focus on skills rather than concepts, but in general I respect Fred's point that different things can be useful for different students. Perhaps the most important thing is to be clear from the beginning on what we expect the students to learn during the semester.
Now, to make a meta-comment on this: I'm basing these statements on my own experiences and have not done a study of the effectiveness of these different teaching ideas. I'd like to, though. And I have read some reviews of the literature on teaching.
Anonymous: I agree about the reputational spillover. I've just seen some examples where I think the spillover has been abused so I try to be more careful. But that's just a choice to make. Newspaper columnists have a role to play, as do scientists. And there's no reason that people have to be limited by any particular role, even if I choose to do so.
The book in response to "The Bell Curve", by members of the Carnegie Mellon Stats department is:
"Intelligence, Genes, and Success: Scientists Respond to The Bell Curve" (Devlin, Fienberg, Resnick, Roeder)
http://www.amazon.com/exec/obidos/ASIN/0387949860…
Thanks to Scott for the citation. I went through some of this material back in the day, but, as most anyone who follows this topic closely can tell you, the material there is thin gruel.
The whole topic, especially in regards to advances in genetic analysis, is a fascinating one. Perhaps Sam or Andrew will blog more about it in the future.
What! Admitting you're not omnisicient? What on earth are you blogging for then?
More seriously you're setting the bar far too high. If asked to comment in the media on some topic where your general statistical training and analytic ability adds value you should, whether or not the issue involves your particular speciality. Because rest assured if you don't then the comment will be provided instead by someone without that training or ability.