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

Discussion of “A probabilistic model for the spatial distribution of party support in multiparty elections”

From 1994. I don’t have much to say about this one. The paper I was discussing (by Samuel Merrill) had already been accepted by the journal—I might even have been a referee, in which case the associate editor had decided to accept the paper over my objections—and the editor gave me the opportunity to publish […]

Review of “Forecasting Elections”

From 1993. The topic of election forecasting sure gets a lot more attention than it used to! Here are some quotes from my review of that book by Michael Lewis-Beck and Tom Rice: Political scientists are aware that most voters are consistent in their preferences, and one can make a good guess just looking at […]

Poker math showdown!

In comments, Rick Schoenberg wrote: One thing I tried to say as politely as I could in [the book, "Probability with Texas Holdem Applications"] on p146 is that there’s a huge error in Chen and Ankenman’s “The Mathematics of Poker” which renders all the calculations and formulas in the whole last chapter wrong or meaningless […]

How Many Mic’s Do We Rip

Yakir Reshef writes: Our technical comment on Kinney and Atwal’s paper on MIC and equitability has come out in PNAS along with their response. Similarly to Ben Murrell, who also wrote you a note when he published a technical comment on the same work, we feel that they “somewhat missed the point.” Specifically: one statistic […]

My courses this fall at Columbia

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. […]

“Psychohistory” and the hype paradox

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 […]

Luck vs. skill in poker

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 […]

How do you interpret standard errors from a regression fit to the entire population?

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 […]

Discussion with Sander Greenland on posterior predictive checks

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 […]

Correlation does not even imply correlation

The above title is my response to a discussion that began with this email sent to be by Steve Roth: Noah Smith had a great tweet recently, a real keeper for me [Roth]. Causation is correlated with correlation. I would reword it: Correlation correlates with causation. (Just not very much.) And I wonder if the […]