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Archive of posts filed under the Miscellaneous Statistics category.

When we talk about the “file drawer,” let’s not assume that an experiment can easily be characterized as producing strong, mixed, or weak results

Neil Malhotra: I thought you might be interested in our paper [the paper is by Annie Franco, Neil Malhotra, and Gabor Simonovits, and the link is to a news article by Jeffrey Mervis], forthcoming in Science, about publication bias in the social sciences given your interest and work on research transparency. Basic summary: We examined […]

Pre-election survey methodology: details from nine polling organizations, 1988 and 1992

This one from 1995 (with D. Stephen Voss and Gary King) was fun. For our “Why are American Presidential election campaign polls so variable when votes are so predictable?” project a few years earlier, Gary and I had analyzed individual-level survey responses from 60 pre-election polls that had been conducted by several different polling organizations. […]

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 in room 428 Pupin Hall: 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, […]

“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 […]