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Archive of posts filed under the Miscellaneous Statistics category.

What to do in 2015: Your statistics diary

For the last two weeks of our class on statistical communication, I gave my students the following assignment: Every day, you will write an entry in your statistics diary. Just set up a text or Word file and add to it each day. The diary entries can be anything. They can be short slice-of-life observations […]

“Why continue to teach and use hypothesis testing?”

Greg Werbin points us to an online discussion of the following question: Why continue to teach and use hypothesis testing (with all its difficult concepts and which are among the most statistical sins) for problems where there is an interval estimator (confidence, bootstrap, credibility or whatever)? What is the best explanation (if any) to be […]

Stethoscope as weapon of mass distraction

Macartan Humphreys sent me a Shiny app demonstrating you can get statistical significance from just about any pattern of random numbers. I posted it, and, in response, commenter Rahul wrote: It sure is a cute demo but it’s a bit like insinuating a doctor’s stethoscope is useless by demonstrating ten ways in which it can […]

A New Year puzzle from Macartan Humphreys

Macartan writes: There is a lot of worry about publication and analysis bias in social science research. It seems results are much more likely to be published if they are statistically significant than if not which can lead to very misleading inferences. There is some hope that this problem can be partly addressed through analytic […]

Statistical methods as pocket tools

I was inspired by this post by John Cook, “People want Swiss Army Knives,” to think more generally about the idea of statistical methods as pocket tools. Cook argues that the Swiss Army Knife is a more useful tool than a scalpel because it can do so many more things, even if it does none […]

Common sense and statistics

John Cook writes: Some physicists say that you should always have an order-of-magnitude idea of what a result will be before you calculate it. This implies a belief that such estimates are usually possible, and that they provide a sanity check for calculations. And that’s true in physics, at least in mechanics. In probability, however, […]

Using statistics to make the world a better place?

In a recent discussion involving our frustration with crap research, Daniel Lakeland wrote: I [Lakeland] really do worry about a world in which social and institutional and similar effects keep us plugging away at a certain kind of cargo-cult science that produces lots of publishable papers and makes it easier to get funding for projects […]

Research benefits of feminism

Unlike that famous bank teller, I’m not “active in the feminist movement,” but I’ve always considered myself a feminist, ever since I heard the term (I don’t know when that was, maybe when I was 10 or so?). It’s no big deal, it probably just comes from having 2 big sisters and growing up during […]

The Use of Sampling Weights in Bayesian Hierarchical Models for Small Area Estimation

All this discussion of plagiarism is leaving a bad taste in my mouth (or, I guess I should say, a bad feeling in my fingers, given that I’m expressing all this on the keyboard) so I wanted to close off the workweek with something more interesting. I happened to come across the above-titled paper by […]

Message to Booleans: It’s an additive world, we just live in it

Boolean models (“it’s either A or (B and C)”) seem to be the natural way that we think, but additive models (“10 points if you have A, 3 points if you have B, 2 points if you have C”) seem to describe reality better—at least, the aspects of reality that I study in my research. […]