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Archive of posts filed under the Miscellaneous Statistics category.

“In general I think these literatures have too much focus on data analysis and not enough on data collection.”

Mike Zyphur pointed me to an article appearing in Psychological Bulletin with a meta-analysis of ovulatory cycle effects: Title: Do Women’s Mate Preferences Change Across the Ovulatory Cycle? A Meta-Analytic Review Authors: Gildersleeve, K; Haselton, MG; Fales, MR Source: PSYCHOLOGICAL BULLETIN , 140 (5):1205-1259; SEP 2014 Abstract: Scientific interest in whether women experience changes across […]

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 […]

“Voices from everywhere saying gently: This we praise. This we don’t.”

One of America’s leading political columnists, David Brooks, has just come out with a column called “The Cost of Relativism” about the growing chasm between college-educated America and those who write for major newspapers. It’s got a definitive collection of data about this divide. Just kidding about the “definitive collection of data.” Anyway, to continue: […]

Interactive demonstrations for linear and Gaussian process regressions

Here’s a cool interactive demo of linear regression where you can grab the data points, move them around, and see the fitted regression line changing. There are various such apps around, but this one is particularly clean: (I’d like to credit the creator but I can’t find any attribution at the link, except that it’s […]

“The Saturated Fat Studies: Set Up to Fail”

Russ Lyons points me to this recent magazine article by Martijn Katan and a research article, “Diet and Serum Cholesterol: Do zero correlations negate the relationship?” by David Jacobs, Joseph Anderson, and Henry Blackburn, and this video by Michael Greger. This is interesting stuff, especially as the ultimate truth is still very unknown. It’s good […]

These are the statistics papers you just have to read

Here. And here. Just kidding. Here’s the real story. Susanna Makela writes: A few of us want to start a journal club for the statistics PhD students. The idea is to read important papers that we might not otherwise read, maybe because they’re not directly related to our area of research/we don’t have time/etc. What […]

What hypothesis testing is all about. (Hint: It’s not what you think.)

I’ve said it before but it’s worth saying again. The conventional view: Hyp testing is all about rejection. The idea is that if you reject the null hyp at the 5% level, you have a win, you have learned that a certain null model is false and science has progressed, either in the glamorous “scientific […]

“Precise Answers to the Wrong Questions”

Our friend K? (not to be confused with X) seeks pre-feedback on this talk: Can we get a mathematical framework for applying statistics that better facilitates communication with non-statisticians as well as helps statisticians avoid getting “precise answers to the wrong questions*”? Applying statistics involves communicating with non-statisticians so that we grasp their applied problems […]

“The harm done by tests of significance” (article from 1994 in the journal, “Accident Analysis and Prevention”)

Ezra Hauer writes: In your January 2013 Commentary (Epidemiology) you say that “…misunderstanding persists even in high-stakes settings.” Attached is an older paper illustrating some such. “It is like trying to sink a battleship by firing lead shot at it for a long time”—well put!

“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 […]