1
Suspicious data pattern in recent Venezuelan election
Here’s a little “fake stats in the wild” gem that I think you and your followers will find at the least somewhat amusing.
Andrew Gelman
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2
Bayesian Statistics: The three cultures
A traditional subjective Bayesian will assume a data generating distribution (aka a likelihood when viewed as a function of the parameters). Then, conditional on this assumption, they encode their prior beliefs as a prior distribution over parameters. After this, they turn the crank on posterior inference and don’t…
3
ML is not that good at predicting consumers' choices
I wanted to share the attached paper on choice prediction that I recently co-authored with Itamar Simonson in case it’s of interest.
4
Bayesians moving from defense to offense
Erik van Zwet, Sander Greenland, Guido Imbens, Simon Schwab, Steve Goodman, and I write :
5
They say that stocks go down during the day and up at night
Prompted by your blog post this morning, I attach a plot from Figure 3 of They Still Haven’t Told You showing overnight and intraday returns to AIG (with logarithmic vertical scale, updated with data through the end of October).
6
Reverse-engineering the problematic tail behavior of Fivethirtyeight forecast
We’ve been writing a bit about some odd tail behavior in the Fivethirtyeight election forecast, for example that it was giving Joe Biden a 3% chance of winning Alabama (which seemed high), it was displaying Trump winning California as in “the range of scenarios our model thinks is possible” (which didn’t seem right)…
7
A baffling scale transform on a chart of university course selection trends
Harvard Magazine printed the following chart that confirms a trend in undergraduate majors that we all know about: students are favoring STEM majors at the expense of humanities.
8
What’s Wrong with Bayes
My problem is not just with the methods—although I do have problems with the method—but also with the ideology.
9
I disagree with Turing and Kahneman regarding statistical evidence (2014)
It’s funny. I’m the statistician, but I’m more skeptical about statistics, compared to these renowned scientists.
10
Dumb statistical models, always making people look bad
This is Jessica. In my Prediction for Decision-making class last quarter we talked about human predictions and decisions relative to algorithmic ones. This led to a discussion about why it’s often hard to demonstrate the value of human knowledge once you have a decent statistical model.
11
One night in Uzbekistan: Why was this one data point so influential?
We have a comment coming out in Nature next week that is going to cause the retraction of a high-profile paper by Kotz et al. from last year (the second most cited climate paper in the news in 2024).
12
How to Think about Correlation?
I am an economist at the Federal Trade Commission with a very basic statistics question, one that I have put to several fairly high-powered econometricians, and to which no one has had a satisfying answer.
13
Holes in Bayesian Statistics
Every philosophy has holes, and it is the responsibility of proponents of a philosophy to point out these problems. Here are a few holes in Bayesian data analysis: (1) the usual rules of conditional probability fail in the quantum realm, (2) flat or weak priors lead to terrible inferences about things we care about…