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
A flawed paper in management science has been cited more than 6k times
In a post entitled, “How Institutional Failures Undermine Trust in Science: The Case of a Landmark Study on Sustainability and Stock Returns,” Andy King (my collaborator on the project on scheduled post-publication review ) tells a disturbing story of the failure of the scholarly publication process :
3
“AI promised to revolutionize radiology but so far its failing”
Geoffrey Hinton is a legendary computer scientist . . . Naturally, people paid attention when Hinton declared in 2016, “We should stop training radiologists now, it’s just completely obvious within five years deep learning is going to do better than radiologists.” The US Food and Drug Administration (FDA) approved the…
4
So much of academia is about connections and reputation laundering
1. Statistics / numerical analysis / data science is a lot harder than you, the reader of this blog, might think.
5
Open AI gets GPT-3 to work by hiring an army of humans to fix GPT’s bad answers
A few months ago, Smith wrote an AI-skeptical article where he threw some sentences at the GPT-3, a text processor from Open AI. As wikipedia puts it:
6
False claims in a widely-cited paper
A couple months ago we had a post, This paper in Management Science has been cited more than 6,000 times. Wall Street executives, top government officials, and even a former U.S. Vice President have all referenced it. It’s fatally flawed, and the scholarly community refuses to do anything about it. which was about…
7
Chief scientist of major corporation can’t handle criticism of the work he hypes
A correspondent who wishes to remain anonymous points us to this article in Technology Review , “Why Meta’s latest large language model survived only three days online. Galactica was supposed to help scientists. Instead, it mindlessly spat out biased and incorrect nonsense.” Here’s the story:
8
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…
9
If you think psychological science is bad, imagine how bad it was in 1999
Shane Frederick points us to this article from 1999 , “Stereotype susceptibility: Identity salience and shifts in quantitative performance,” about which he writes:
10
The claimed effect size is about a zillion times higher than is plausible
Some years ago, you blogged about a research article by Hasan and colleagues (2013) .
11
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.
12
The immediate victims of a con would rather act as if the con never happened
Dorothy Bishop has the story about “a chemistry lab in CNRS-Université Sorbonne Paris Nord”:
13
Concerns with that Stanford antibody study of coronavirus prevalence
I’ve been following your blog for a while and checked in today to see if there was a thread on last week’s big-splash Stanford antibody study (the one with the shocking headline that they got 50 positive results in a “random” sample of 3330 antibody tests, suggesting that nearly 2% of the population has been infected…
14
It’s not just p=0.048 vs. p=0.052
Peter Dorman points to this post on statistical significance and p-values by Timothy Taylor, editor of the Journal of Economic Perspectives, a highly influential publication of the American Economic Association.
15
Bayesians moving from defense to offense
Erik van Zwet, Sander Greenland, Guido Imbens, Simon Schwab, Steve Goodman, and I write :
16
Noted study in psychology fails to replicate, crumbles with evidence of fraud
About 80 people pointed me to this post by Uri Simonsohn, Joe Simmons, and Leif Nelson about a 2012 article, “Signing at the beginning makes ethics salient and decreases dishonest self-reports in comparison to signing at the end.” Apparently some of the data in that paper were faked; see for example here:
17
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).
18
I disagree with Geoff Hinton regarding "glorified autocomplete"
“People say, It’s just glorified autocomplete . . . Now, let’s analyze that. Suppose you want to be really good at predicting the next word. If you want to be really good, you have to understand what’s being said. That’s the only way. So by training something to be really good at predicting the next word, you’re…
19
A Post Mortem on the Gino Case
Zoe Ziani, a psychology researcher who had the misfortune several years ago as a Ph.D. student be tasked with following up on some unrelicable published psychology research, tells the story of how her department pulled the chair out from under her:
20
Do simpler machine learning models exist and how can we find them?
The above is the title of a talk by computer scientist Cynthia Rudin. here’s the abstract:
21
Every modeler is supposed to be a great Python programmer
This post is by Phil Price, not Andrew. I’ve had a run of luck ever since I left my staff scientist position at Lawrence Berkeley Laboratory to become a freelance consultant doing statistical modeling and forecasting, mostly related to electricity consumption and prices: just as I finished a contract, another one…
22
“Chatbots: Still Dumb After All These Years”
In 1970, Marvin Minsky, recipient of the Turing Award (“the Nobel Prize of Computing”), predicted that within “three to eight years we will have a machine with the general intelligence of an average human being.”
23
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)…
24
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.
25
A homework question in someone’s 11th grade statistics class
My son is in 11th grade. Below you’ll find a HW question which was given in my son’s statistics class. How would you answer?
26
Let’s Publish Everything
The other day someone pointed me to this article by James Kaufman and Vlad Glǎveanu in a psychology journal which begins:
27
Nicholas Polson has authored 258 academic papers in 2026 so far
Nicholas Polson has, by my count using his SSRN page, already written 258 working papers in 2026 alone. He’s already written (or at least published to SSRN), six papers today, August 26, 2026.
28
What major works of literature were written after age of 85? 75? 65?
EDIT: removed a couple of false positives based on comments from people. 2/04/2026: added a GitHub repository with data for this post
29
High-intensity exercise, some new news
Several months I noticed something interesting (to me!) about my heart rate, and I thought about blogging about it…but I didn’t feel like it would be interesting (to you!) so I’ve been hesitant. But then the NYT published something that is kinda related and I thought OK, what the hell, maybe it’s time for an update…
30
The polls messed up
To continue our post-voting, pre-vote-counting assessment (see also here and here ), I want to separate two issues which can get conflated: 1. Problems with poll-based election forecasts.