Comments on: Lies, damn lies

By: LarryH

LarryH — Wed, 20 Oct 2004 11:43:03 +0000

It appears that you’ve taken stats courses which are geared to humanities-oriented bullshitters. My background is in science and technology(B.S.Ch.E.) Would you believe this?… people in technical areas can actually make halfway SENSE out of various statitical criteria! A corollary to the expression “Get a life” might be summed up by “Get a meaningful perspective.” My advice: find a stats course that’s not populated by student and instructor SLACKERS.

By: Tobias Schwarz

Tobias Schwarz — Mon, 18 Oct 2004 00:10:41 +0000

The questions statisticians dread; ‘but WHY did you do that?’ and ‘what does it MEAN?’. Why is it, that when you ask a statistician one of these questions they look at you as if you’ve addressed them in ancient Greek? Strange, I had to take stats classes at the LSE, too, and I liked them much more than anything I had done previously in this area not just because the teaching was great but also because they usually provided answers to the questions you mention here.

By: Cogan

Cogan — Sun, 17 Oct 2004 08:24:24 +0000

Huh. I must have been really lucky. I took a few lower-division stats courses at UC Berkeley and found them surprisingly interesting and always well taught. I didn’t have too much trouble grasping the basic concepts or learning the little bit of linear algebra required, and I’m not even a math geek. The Freedman/Pisani/Purvis textbook is good at explaining the concepts but skimps too much on those very useful formulas. Other good textbooks are Multivariate Statistics by Sam Kachigan, and Modern Elementary Statistics by John Freund, both of which give you the formulas. I also enjoyed The Pleasures of Probability by Richard Isaac. Maybe I’m weird, but I found stats and prob downright fun, because it’s so damn counterintuitive. Its results often defy your commonsense expectations. I regret now I didn’t take more stats courses.

By: Fluffy

Fluffy — Sat, 16 Oct 2004 03:03:01 +0000

I enjoyed reading Maria’s comments. My perspective about teaching technical topics to non-technical people is: 1. Don’t lie. If you really need algebra, then tell students they need algebra. If they need calculus, tell them you need calculus. Be up front. 2. Present a few formulas, but not too many. Any Ph.D. student in a decent American university in social sciences should be able to handle some algebra. For crying out loud – they are a “Ph.D.” student!! Asking for some algebra is really not all that much. Have some standards!! Expect a high school level education from people. On the other hand, don’t get lost in equations. Statistics is about “inference” – got that? If you want math, go to a different department. We do statistics because it helps us reason about a complex world. So don’t drench the class in equations, but explain how statistics helps us make choices. 3. Do a lot of “real” examples. Download some GSS or NES data. Don’t use silly text book examples. Use data that social scientists might really be interested in. That’s my $.02

By: Jason Grossman

Jason Grossman — Fri, 15 Oct 2004 19:24:23 +0000

Oh, P.S. I write about this stuff for a living (I’m on the faculty at a good university), and I’ve taught it to undergrads, so even if you suspect I’m wrong you probably find it interesting to know that there are people who do understand statistics and still think it’s gibberish (as currently practised).

By: Jason Grossman

Jason Grossman — Fri, 15 Oct 2004 19:20:41 +0000

I agree with this: “‘g’ has it right. The whole apparatus of significance tests, confidence intervals and so on is a load of mumbo-jumbo.” But I’m not just posting to say “me too”. I’m posting to say that if we’re right that the apparatus of statistics (currently) makes no sense, no wonder it’s no fun to learn. I think what we have is NOT mainly a pedagogical problem. Sure there are pedagogical problems, but they exist in other subjects too, and in some cases are just as bad. What makes statistics so special is that your teachers don’t KNOW why the methods they’re teaching you make sense, and the reason they don’t know that is that the DON’T make sense!

By: Alex Fradera

Alex Fradera — Fri, 15 Oct 2004 13:15:32 +0000

Agree Feynman is another good way to get some statistical thinking. Some statistical namedropping (pointless I know, but when else do you get a chance to do this?) – Jonckheere hangs out at my department and I have workshopped stats with him (and THAT is a fun way to meet the subject head on) – a living legend of stats. Our dep is quite cool for its stats heritage, what with Spearman to boast about (and Fisher down the road at the genetics dept).

By: Maria

Maria — Fri, 15 Oct 2004 09:25:16 +0000

Hi all, sorry to have stepped out of comments – just the tiny matter of actually doing that exam… which I’m not sure I passed. Oh well, if I have to re-sit, maybe next time I’ll start to get it!

By: Patrick

Patrick — Fri, 15 Oct 2004 01:59:23 +0000

My personal pet peeve here- The reason statisticians often give you mathematical gibberish in response to a social science student’s question of “but what does it all MEAN?” is because the mathematical gibberish is about 100 times better at answering the question than anything they could put into words. I’m reminded of a class conversation I had in law school. There were some numbers about different stop and frisk policies, and there was dispute as to whether these numbers showed an increase of 2% in a particular effect, or a 20% increase. This seemed to make a lot of difference to people. It was the dumbest discussion ever. The raw data was 10% originally, then 12% afterwards. Increase of 2%? Or 20% increase? BOTH. Come on. It just depends on how you want to articulate what the numbers say. And frankly, knowing the numbers is a LOT more informative than just hearing “20% increase.” 10% to 12% is a 20% increase. It’s also an increase of 2% raw. It makes a difference how you describe these things in how people will understand the data. They hear 2%, they think small increase. They hear 20%, they might think big increase. But, neither explanation is inherently better than the other. So many people were convinced that there was a “right” way to articulate this. There wasn’t. The closest thing to a “right way” would be to repeat the original numbers. Statisticians know this, and they get leery of telling you something in words when they think you might draw a false conclusion. So try to give them some credit on it. They’re not being obscure, they’re being accurate. This may be frustrating for social science students who want the verbal answer, but sometimes the verbal answer is less useful if you’re goal is accuracy. Oh, and graphing a quadratic is taught to college preparatory students at 10th grade, and some students as early as 7th or 8th. So the instructor was probably being honest when he made his comment about basic arithmetic.

By: roublen vesseau

roublen vesseau — Fri, 15 Oct 2004 01:33:10 +0000

Last post, but I thought of two more books which might be helpful in developing a statistics intuition: Richard Fenyman’s two autobiographies, “Surely You’re Joking, Mr. Feynman!” and “What Do You Care What Other People Think?”. They’re both very funny, but I think there is a lot of probability-thinking in it, especially in his discussion of the failure of the Challenger shuttle, and the differences in mindset between the top managers and the lower level engineers.

By: Ethesis

Ethesis — Fri, 15 Oct 2004 01:31:23 +0000

Ok, I enjoyed statistics, at least the second class, I found the first class’s grading frustrating. Now, I’ve got to confess they designed the advanced statistic’s final just for me (I was ten points ahead of the next highest grade out of any of the sections who took the final, who was ten points about the “A” grade cluster), but … Statistics can be taught without being terribly painful. Our school used, for the most part, Econ grad students who taught for 3-4 years and who were always fresh, invigorated and engaged (and the only non-tenured people teaching any intro class to Econ. My other intro class profs included the guy who became department chair and a full professor). The key is to love the subject. I had been out of school for two years (doing volunteer church work) before that first stats class, and a speech major before that, so I wasn’t a math geek going in, in spite of any aptitude for the subject. But what made it work, and what led to a 90% pass rate or so (in a department that had an average gpa of 1.98—so they weren’t exactly passing everyone) was engaged instructors who liked the topic. And good textbooks. If you want to make tenure, use good textbooks.

By: Jonathan Goldberg

Jonathan Goldberg — Fri, 15 Oct 2004 00:04:02 +0000

It’s hard to answer the question: what do you do when you’ve given a logical explanation of something mathematical, such as a statistical concept, and the student still doesn’t get it. The usual approach is to repeat the same explanation more slowly. This seems to be an application of the Ned Land school of linguistics. In the opinion of Mr. Land (the harpooner in Twenty Thousand Leagues Under the Sea) “It’s a mighty stupid native who can’t understand English spoken loud and slow.” It works about as well here as it usually does. I’m pleased to see from some of the postings above that real work is being done on this problem. One problem with books written by mathematicians is that mathematicians are poets. It pains them to put on paper anything not strictly necessary to make the point at hand. This results in the “lapidary style,” which is wonderful for them and torture for everyone else. But there are exceptions. This post was prompted by the mention of Gilbert Strang’s open courseware Linear Algebra site. I haven’t seen it, but I’ll bet it’s wonderful. I think this because, after having taken (and even passed) a course in it, I learned what I know about Linear Algebra from Strang’s Applied Linear Algebra. This is THE BEST MATH TEXTBOOK EVER. It’s astonishing how much Strang can clarify things with a few sentences or even a few words of motivation: “the natural way to think about this type of problem is this because…” I think that anyone writing a text on a mathematical subject for anyone other than other mathematicians should be required to memorize Strang’s book first. I was especially impressed with his development of the usual least squares formula without calculus, starting from the idea of “the line closest to the data.” I’d always seen this done using the usual calculus-based minimization method. Doing it without calculus was a revelation I still remember twenty years later.

By: Patrick

Patrick — Thu, 14 Oct 2004 21:43:40 +0000

Matt…Wonacott & Wonacott is a classic! I second your choice. agm, I’m with you. I’m a Research Consultant working with academics in a public university in Texas. The mathematicians I work with on computing issues regularly laugh at me and my background in social science statistics (econometrics, political methods, and psychological methods). To them, statistics is some voodoo that detracts from number theory and matrix algebra. All of our statistics courses are taught in the different departments (i.e. econometrics in Economics, political methods in Political Science, and psychological methods in Psychology). When I started my Master’s about 6 years ago, I was horrified by statistics. I sucked at them despite having a background in engineering stats from my undergrad days. Now I work with them on a daily, comfortable basis and I write code for several different stats platforms. It is odd how the worm can turn…

By: Cranky Observer

Cranky Observer — Thu, 14 Oct 2004 21:16:09 +0000

One more observation: of the 100 or so undergraduate and gradute classes I have taken in my life, I use two weekly if not daily: Engineering Probability and Intermediate Political Theory. I do more technical work than most, but nonetheless having a basic understanding of probability is critical to job success IMHO. Cranky

By: agm

agm — Thu, 14 Oct 2004 20:31:21 +0000

I gotta go with jam on this one. I’m actually surprised to hear people say that stats was/is considered a subfield of math, because back home it was regularly mentioned that the two fields were mortal (or at least methodological) enemies. If I understand correctly, the only people mathematicians hate more for the abuse we do to math is we physicists (think chain rule, or the derivative as a ratio of two differentials, or the integral of zero must be zero, or …). numerical fucking analysis; (or solicit in whatever other way presents itself): ROTFLMFAO. It’s criminal to teach statistics without mentioning that Student was on Guiness’s payroll. And just to show that I’m an evil physicist, two words: statistical mechanics. Enjoy =).