Lon-Capa is web-based software for doing homework, and much more. It’s amazing what it can do. It’s also amazing how hard it is to figure out how to do anything. I finally figured out how to get started from these Lon-Capa mini-lessons by Daniel Sewell. I couldn’t even get started, until I realized one had to click on “switch server” in order to create homework problems.

There is a GUI problem creator in Lon-Capa, but I prefer to write things in the source code (XML in this case). That way, you can cut and paste to create new problems, rather than clicking. So below is my attempt to understand how to create problems from scratch. The material here tries to abstract the relevant info from the Lon-Capa author manual.
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From Business Week.

I’ve always thought the fetish for calculus was misplaced. Apparently, the president of the National Council of Teachers of Mathematics, J. Michael Shaughnessy, agrees. Anybody going into higher mathematics of course needs a solid grounding in calculus, but for the other 90%, or 99%, focussing on calculus to the exclusion of statistical thinking is counterproductive. How many news stories mislead readers because of incorrectly calculated spherical shells? How many because of bad statistical reasoning?

Via dangerousmeta

A spate of articles in respected (i.e., not Fox) publications have appeared recently that seem to cast doubt on the scientific method, or at least on statistical side of it:

The New Yorker: The Truth Wears Off
The Atlantic: Lies, Damned Lies, and Medical Science
The New York Times: Journal’s Paper on ESP Expected to Prompt Outrage: The outrage

A brief summary of the articles: Results of many statistical studies, each certified with the 5% significance stamp of approval, turn out on further research to be wrong.
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Discovery News reported on a study that found kids who watch more TV tend to have more psychological difficulties like relating to peers, and that the difficulties occurred even if the kid also participated in physical activity. The story states that watching TV caused the problems, so my antennae went up: How do they know the difficulties relating to peers didn’t cause more TV watching? Continue reading →

In the story about Research 2000, a polling firm was caught out when statisticians noticed the data was not random enough. There have been other, more famous cases, where lack of enough randomness cast some doubt on statistical results.
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Can we trust political pollsters? There is no agency, like the FDA or Moody’s (trust them?), that audits polling companies to see if they are conducting polls they way they say they are. An obvious method of assessment is to compare their predictions to outcomes of actual elections, but elections occur only once in a while, and polling on, e.g., presidential approval never receives a genuine check.
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Researchers have long known that Alzheimer’s is associated with “plaques” (sticky clumps of proteins), hence getting rid of (or preventing development of) the plaques would seem to cure or at least slow down the symptoms of the disease. New research suggests that the plaques are actually the body’s response to “oligomers” (free-floating clumps of protein, and Swedish cousin of Gomer Pyle), i.e., the oligomers cause the Alzheimer’s, and the plaques are trying to sequester the oligomers to protect the brain. Thus the drugs targeting the plaques may indeed be making things worse.
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In the study discussed below, people who were life-long alcohol abstainers were not accepted into the study. The abstainers in the study were those abstaining at the outset of the study, but not necessarily for their entire lives. Are such life-long abstainers different in additional ways from just current abstainers? Maybe. Maybe that difference could partially explain why heavy drinkers were seen to (slightly, non-significantly) outlive abstainers. E.g., some lifelong abstainers could be so for religious reasons, which reasons also lead to other healthy behaviors (no smoking, no caffeine, as Mormons).

Student’s t is one of the greatest statistics of all time, no question a first ballot hall-of-famer. I am especially fond of the t as its distribution was first published in 1908 (the most recent time the Cubs won the World Series), and the author Student, aka W. T. Gosset, had developed the t in order to brew better Guinness. (Wikipedia entry.) But is it necessary to teach it in the first elementary statistics course? Second course, certainly, or a more advance beginning course, but for a liberal-arts-ish course?

I say no. Continue reading →