Skip to content
Archive of posts filed under the Miscellaneous Statistics category.

Six quick tips to improve your regression modeling

It’s Appendix A of ARM: A.1. Fit many models Think of a series of models, starting with the too-simple and continuing through to the hopelessly messy. Generally it’s a good idea to start simple. Or start complex if you’d like, but prepare to quickly drop things out and move to the simpler model to help […]

“The Statistical Crisis in Science”: My talk this Thurs at the Harvard psychology department

Noon Thursday, January 29, 2015, in William James Hall 765 room 1: The Statistical Crisis in Science Andrew Gelman, Dept of Statistics and Dept of Political Science, Columbia University Top journals in psychology routinely publish ridiculous, scientifically implausible claims, justified based on “p < 0.05.” And this in turn calls into question all sorts of […]

The (hypothetical) phase diagram of a statistical or computational method

So here’s the deal. You have a new idea, call it method C, and you try it out on problems X, Y, and Z and it works well—it destroys the existing methods A and B. And then you publish a paper with the pithy title, Method C Wins. And, hey, since we’re fantasizing here anyway, […]

“What then should we teach about hypothesis testing?”

Someone who wishes to remain anonymous writes in: Last week, I was looking forward to a blog post titled “Why continue to teach and use hypothesis testing?” I presume that this scheduled post merely became preempted by more timely posts. But I am still interested in reading the exchange that will follow. My feeling is […]

What’s the point of the margin of error?

So . . . the scheduled debate on using margin of error with non-probability panels never happened. We got it started but there was some problem with the webinar software and nobody put the participants could hear anything. The 5 minutes of conversation we did have was pretty good, though. I was impressed. The webinar […]

Lee Sechrest

Yesterday we posted on Lewis Richardson, a scientist who did pioneering work in weather prediction and, separately, in fractals, in the early twentieth century. I was pointed to Richardson by Lee Sechrest, who I then googled. Here’s Sechrest’s story: His first major book [was] “Psychotherapy and the Psychology of Behavior Change” . . . Sechrest […]

Lewis Richardson, father of numerical weather prediction and of fractals

Lee Sechrest writes: If you get a chance, Wiki this guy: I [Sechrest] did and was gratifyingly reminded that I read some bits of his work in graduate school 60 years ago. Specifically, about his math models for predicting wars and his work on fractals to arrive at better estimates of the lengths of common […]

When a study fails to replicate: let’s be fair and open-minded

In a recent discussion of replication in science (particularly psychology experiments), the question came up of how to interpret things when a preregistered replication reaches a conclusion different from the original study. Typically the original, published result is large and statistically significant, and the estimate from the replication is small and not statistically significant. One […]

Artist needed!

We have some great ideas but none of us can draw. We need your help with designs and art for any or all of these projects: 1. “Gone Fishing” T-shirt A person is standing in a boat, fishing. The lake is full, not of fish but of little numbers: “.14″, “.31″, “.08″, etc etc. And […]

What’s misleading about the phrase, “Statistical significance is not the same as practical significance”

You’ve heard it a million times, the idea is that if you have an estimate of .003 (on some reasonable scale in which 1 is a meaningful effect size) and a standard error of .001 then, yes, the estimate is statistically significant but it’s not practically significant. And, indeed, sometimes this sort of thing comes […]