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Archive of posts filed under the Teaching category.

Why do we communicate probability calculations so poorly, even when we know how to do it better?

Haynes Goddard writes: I thought to do some reading in psychology on why Bayesian probability seems so counterintuitive, and making it difficult for many to learn and apply. Indeed, that is the finding of considerable research in psychology. It turns out that it is counterintuitive because of the way it is presented, following no doubt […]

How can teachers of (large) online classes use text data from online learners?

Dustin Tingley sends along a recent paper (coauthored with Justin Reich, Jetson Leder-Luis, Margaret Roberts, and Brandon Stewart), which begins: Dealing with the vast quantities of text that students generate in a Massive Open Online Course (MOOC) is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as MOOC […]

A rare topical post

Harvey Motulsky writes: Every year at passover, I struggle to peel two dozen hard boiled eggs and search the web to see if there isn’t a trick to do it better. But all the hits say the same thing: put the eggs in cold water, then bring to a boil. But this guy [J. Kenji […]

Time-release pedagogy??

Mark Palko points to this report and writes: Putting aside my concerns with the “additional years of learning” metric (and I have a lot of them), I have the feeling that there’s something strange here or i’m missing something obvious. That jump from 3-year impact to 4-year seems excessive. The press release links to a […]

Regression: What’s it all about? [Bayesian and otherwise]

Regression: What’s it all about? Regression plays three different roles in applied statistics: 1. A specification of the conditional expectation of y given x; 2. A generative model of the world; 3. A method for adjusting data to generalize from sample to population, or to perform causal inferences. We could also include prediction, but I […]

Define first, prove later

This post by John Cook features a quote form a book “Calculus on Manifolds,” by Michael Spivak which I think was the textbook for a course I took in college where we learned how to prove Stokes’s theorem, which is something in multivariable calculus involving the divergence and that thing that you get where you […]

New time unit needed!

We need a time unit that’s bigger than a minute but smaller than an hour. I thought of it when writing this comment in which I referred to “2100 valuable minutes of classroom time” during the semester (that’s 75 minutes per class, twice a week, for 14 weeks). A minute of class time is pretty […]

Stock-and-flow and other concepts that are important in statistical modeling but typically don’t get taught to statisticians

Bill Harris writes: You’ve written about causality somewhat often, and you, along with perhaps everyone who has done anything with statistics, have written that “correlation is not causation.” When you say that correlation is not causation, you seem to be pointing out cases where correlation exists but causality does not. While that’s important, there’s another […]

“A small but growing collection of studies suggest X” . . . huh?

Lee Beck writes: I’m curious if you have any thoughts on the statistical meaning of sentences like “a small but growing collection of studies suggest [X].” That exact wording comes from this piece in the New Yorker, but I think it’s the sort of expression you often see in science journalism (“small but mounting”, “small […]

“Academics should be made accountable for exaggerations in press releases about their own work”

Fernando Martel Garcia points me to this news article by Ben Goldacre: For anyone with medical training, mainstream media coverage of science can be an uncomfortable read. It is common to find correlational findings misrepresented as denoting causation, for example, or findings in animal studies confidently exaggerated to make claims about treatment for humans. But […]