Language Log

I got a message the other day from Laura Petelle, an adjunct professor of philosophy at Illinois Central College, with an optimistic view of the effects of modern technology on writing skills and research abilities, the diametrically opposed to the ill-substantiated pessimism about cellphones destroying language and thought that Naomi Baron somehow peddled to a writer for The Economist. Says Laura:

I've been tutoring writing since I was in high school, and I think texting and instant messaging has made the job quite a bit easier! I used to get students who'd stare at a blank page, for whom writing was a chore, and translating their normal communication mode from talking to writing was like pulling teeth. Today, I get students (both in my college classroom and in the high school tutoring I do on the side) for whom writing IS a normal mode of communication.

Maria Brumm, "Giving the Lie: Blogs and Scientific Criticism", Green Gabbro, 4/6/2008. My favorite paragraph:

This cultural conflict been making the rounds of the geoblogosphere thanks to a pair of editorials in Nature Geoscience on the pros and cons of blogging. See RealClimate and Highly Allochthonous for summaries, Kim (who talks about fact-checking before teaching undergraduates), Chris again (with diagrams!), and James Annan for further discussion. (Incidentally: I am sure the various editors of the Nature Publishing Group are too dignified and professional to dance around their offices going "Oh yeah, baby, who controls the discourse? We control the discourse! UNGH!"… but when was the last time a blog post sparked a rambling article in the pages of EOS or Geology?)

Also worth the price of admission: the pointer to Steven Shapin's A Social History of Truth.

Statistics is full of terms that fool people, because they seem intuitively to mean something very simple, while in fact they mean something equally simple, but radically different. And in the rich lexicon of statistical misunderstanding, few terms are more misleading than "false positive rate".

You take a medical test for Condition X and it comes back positive. Bad news — you have Condition X, right? Not so fast — the test is sometimes wrong. How often? Well, there's a "false positive rate" of 10%. OK, so that means that there's a 10% chance that your positive test result is false, and therefore a 90% chance that you have Condition X, right?

No. Wrong, wrong, wrong.

In this situation, your chances of having Condition X are probably not 9 out of 10, but more like 1 in 10 — or maybe 1 in 1,000 or 1 in 100,000 or even less. Without some additional information, we can't tell what the odds are — but they're almost certainly smaller than 9 in 10, and probably a very great deal smaller. Listen up, and I'll explain.