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Archive of posts filed under the Miscellaneous Statistics category.

Job opening at the U.S. Government Accountability Office

Sam Portnow writes: I am a statistician at the U.S. Government Accountability Office, and we are hiring for a statistician. The full job announcement is below. Personally, I think our office is a really great place to do social science research within the federal government. ———————————————————————- The U.S. Government Accountability Office (GAO) has two vacancies […]

The University of California statistics department paid at least $329,619.84 to an adjunct professor who did no research, was a terrible teacher, and engaged in sexual harassment

I have one of the easy jobs at the university, well paid with pleasant working conditions. It’s not so easy for adjuncts. Ideally, an adjunct professor has a main job and teaches a course on the side, to stay connected to academia and give back something to the next generation. But in an all-too-common non-ideal […]

He wants to test whether his distribution has infinite variance. I have other ideas . . .

Evan Warfel asks a question: Let’s say that a researcher is collecting data on people for an experiment. Furthermore, it just so happens that due to the data collection procedure, data is gathered and recorded in 100-person increments. (Making it so that the researcher effectively has a time series, and at some point t, they […]

Impressions of differential privacy for supreme court justices

This is Jessica. A couple weeks ago Priyanka Nanayakkara pointed me to the fact that Alabama is suing the Census Bureau on the grounds that by using differential privacy it is “intentionally skew[ing] the population tabulations provided to States to use for redistricting” and “forc[ing] Alabama to redistrict using results that purposefully count people in […]

Network of models

Ryan Bernstein shows this demo of a prototype of the network of models visualization in Stan. This is related to the topology of models, an idea that we’ve discussed on occasion and is a key part of statistical workflow that I don’t think is handled well by existing theory or software. What Ryan is doing […]

Still cited only 3 times

I had occasion to refer to this post from a couple years ago on the anthropic principle in statistics. In that post, I wrote: I actually used the anthropic principle in my 2000 article, Should we take measurements at an intermediate design point? (a paper that I love; but I just looked it up and […]

What can the anthropic principle tell us about visualization?

            Andrew’s post on the anthropic principle implies statistical problems are one of three types:  Those that are so easy that you don’t need stats (the signal is very strong relative to noise). Those that require stats because there’s some noise or confounding to be dealt with to recover the […]

The Brazilian Reproducibility Initiative wants your comments on their analysis plan!

Kleber Neves and Olavo Amaral write: We are the coordinators of the Brazilian Reproducibility Initiative, a multicenter systematic replication of experiments from Brazilian biomedical science (the project has been discussed in your blog before via Anna Dreber when we were recruiting participants for our prediction markets). We write now because the first version of our […]

Thinking fast, slow, and not at all: System 3 jumps the shark

By now, we’re all familiar with the three modes of thought. From wikipedia: System 1 is fast, instinctive and emotional. System 2 is slower, more deliberative, and more logical. System 3 is when you say things that sound good but make no sense. System 3 can get activated when you trust what someone tells you […]

New book coming out by Fischer Black!

Gur Huberman has the scoop. At first I was surprised to hear about this, but then I looked up Black on Wikipedia and, hey, he’s only 83, so why not write a book. He also got some prominent academics to promote it, so that’s cool.

What did ML researchers talk about in their broader impacts statements?

This is Jessica. A few months back I became fascinated with the NeurIPS broader impact statement “experiment” where NeurIPS organizers asked all authors to in some way address the broader societal implications of their work. It’s an interesting exercise in requiring researchers to make predictions under uncertainty about societal factors they might not be used […]

If a value is “less than 10%”, you can bet it’s not 0.1%. Usually.

This post is by Phil Price, not Andrew. Many years ago I saw an ad for a running shoe (maybe it was Reebok?) that said something like “At the New York Marathon, three of the five fastest runners were wearing our shoes.” I’m sure I’m not the first or last person to have realized that […]

Formalizing questions about feedback loops from model predictions

This is Jessica. Recently I asked a question about when a model developer should try to estimate the relationship between model predictions and the observed behavior that results when people have access to the model predictions. Kenneth Tay suggested a recent machine learning paper on Performative Prediction by Juan Perdomo Tijana Zrnic. Celestine Mendler-Dunner and […]

Indeed, the standard way that statistical hypothesis testing is taught is a 2-way binary grid. Both these dichotomies are inappropriate.

I originally gave this post the title, “New England Journal of Medicine makes the classic error of labeling a non-significant difference as zero,” but was I was writing it I thought of a more general point. First I’ll give the story, then the general point. 1. Story Dale Lehman writes: Here are an article and […]

Responding to Richard Morey on p-values and inference

Jonathan Falk points to this post by Richard Morey, who writes: I [Morey] am convinced that most experienced scientists and statisticians have internalized statistical insights that frequentist statistics attempts to formalize: how you can be fooled by randomness; how what we see can be the result of biasing mechanisms; the importance of understanding sampling distributions. […]

When can a predictive model improve by anticipating behavioral reactions to its predictions?

This is Jessica. Most of my research involves data interfaces in some way or another, and recently I’ve felt pulled toward asking more theoretical questions about what effects interfaces can or should have in different settings. For instance, the title of the post is one question I’ve started thinking about: In situations where a statistical […]

Is it really true that “the U.S. death rate in 2020 was the highest above normal since the early 1900s—even surpassing the calamity of the 1918 flu pandemic”?

tl;dr. No, it’s not true. The death rate increased by 15% from 2019 to 2020, but it jumped by 40% from 1917 to 1918. But, if so, why would anyone claim differently? Therein lies a tale. A commenter pointed to a news article with the above graphs and the following claim: The U.S. death rate […]

Can you trust international surveys? A follow-up:

Michael Robbins writes: A few years ago you covered a significant controversy in the survey methods literature about data fabrication in international survey research. Noble Kuriakose and I put out a proposed test for data quality. At the time there were many questions raised about the validity of this test. As such, I thought you […]

“Do you come from Liverpool?”

Paul Alper writes: Because I used to live in Trondheim, I have a special interest in this NYT article about exercise results in Trondheim, Norway. Obviously, even without reading the article in any detail, the headline claim that The Secret to Longevity? 4-Minute Bursts of Intense Exercise May Help can be misleading and is subject […]

Conference on digital twins

Ron Kenett writes: This conference and the special issue that follows might be of interest to (some) of your blog readers. Here’s what it says there: The concept of digital twins is based on a combination of physical models that describe the machine’s behavior and its deterioration processes over time with analytics capabilities that enable […]

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