Baby Name Wizard is all over this one. And this all makes me wonder: is there a psychology researcher somewhere with a dog named Stroopy? Probably so. P.S. I just made the mistake of googling “Stroopy.” Don’t do it. I was referri...

Baby Name Wizard is all over this one. And this all makes me wonder: is there a psychology researcher somewhere with a dog named Stroopy? Probably so. P.S. I just made the mistake of googling “Stroopy.” Don’t do it. I was referri...

Below are a bunch of little things I typically mention at some point when I’m teaching my class on how to teach. But my new approach is to minimize lecturing, and certainly not to waste students’ time by standing in front of a group of them, telling them things they could’ve read at their own […] The post Some quick disorganzed tips on classroom teaching appeared first on Statistical Modeling,…

Mon: Some quick disorganzed tips on classroom teaching Tues: Stroopy names Wed: “A hard case for Mister P” Thurs: The field is a fractal Fri: Replication Wiki for economics Sat, Sun: As Chris Hedges would say: Stop me if you’ve heard t...

Stat 6103, Bayesian Data Analysis, TuTh 1-2:30: We’ll be going through the book, section by section. Follow the link to see slides and lecture notes from when I taught this course a couple years ago. This course has a serious workload: each week we have three homework problems, one theoretical, one computational, and one applied. […] The post My courses this fall at Columbia appeared first on Statistical Modeling, Causal…

Lee Wilkinson writes: I thought you might be interested in this post. I was asked about this by someone at Skytree and replied with this link to Tyler Vigen’s Spurious Correlations. What’s most interesting about Vigen’s site is not his video (he doesn’t go into the dangers of correlating time series, for example), but his […] The post “Psychohistory” and the hype paradox appeared first on Statistical Modeling, Causal Inference,…

The thread of our recent discussion of quantifying luck vs. skill in sports turned to poker, motivating the present post. 1. Can good poker players really “read” my cards and figure out what’s in my hand? For a couple years in grad school a group of us had a regular Thursday-night poker game, nickel-dime-quarter with […] The post Luck vs. skill in poker appeared first on Statistical Modeling, Causal Inference,…

I just read this review by Louis Menand of a biography of John Updike. Lots of interesting stuff here, with this, perhaps, being the saddest: When Updike received the National Book Foundation Medal for Distinguished Contribution to American Letters, in 1998, two of [his second wife's] children were present, but his were not invited. Menand’s […] The post Updike and O’Hara appeared first on Statistical Modeling, Causal Inference, and Social…

James Keirstead writes: I’m working on some regressions for UK cities and have a question about how to interpret regression coefficients. . . . In a typical regression, one would be working with data from a sample and so the standard errors on the coefficients can be interpreted as reflecting the uncertainty in the choice […] The post How do you interpret standard errors from a regression fit to the…

Josh Miller writes: I came across your paper in the Journal of Management on unreplicable research, and in it you illustrate a point about the null hypothesis via the hot hand literature. I am writing you because I’d like to move your current prior (even if our work uses a classical approach). I am also […] The post Understanding the hot hand, and the myth of the hot hand, and…

Sander Greenland is a leading epidemiologist and educator who’s strongly influenced my thinking on hierarchical models by pointing out that often the data do not supply much information for estimating the group-level variance, a problem that can be particularly severe when the number of groups is low. (And, in some sense, the number of groups […] The post Discussion with Sander Greenland on posterior predictive checks appeared first on Statistical…