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Archive of posts filed under the Decision Theory category.

Pizzagate, or the curious incident of the researcher in response to people pointing out 150 errors in four of his papers

There are a bunch of things about this story that just don’t make a lot of sense to me. For those who haven’t been following the blog recently, here’s the quick backstory: Brian Wansink is a Cornell University business school professor and self-described “world-renowned eating behavior expert for over 25 years.” It’s come out that […]

Criticism of bad research: More harm than good?

We’ve had some recent posts (here and here) about the research of Brian Wansink, a Cornell University business professor who’s found fame and fortune from doing empirical research on eating behaviors. It’s come out that four of his recent papers—all of them derived from a single experiment which Wansink himself described as a “failed study […]

No guru, no method, no teacher, Just you and I and nature . . . in the garden. Of forking paths.

Here’s a quote: Instead of focusing on theory, the focus is on asking and answering practical research questions. It sounds eminently reasonable, yet in context I think it’s completely wrong. I will explain. But first some background. Junk science and statistics They say that hard cases make bad law. But bad research can make good […]

How to attack human rights and the U.S. economy at the same time

I received this email from a postdoc in a technical field: As you might have heard, Trump signed an executive order today issuing a 30-day total suspension of visas and other immigration benefits for the citizens of Iran and six other countries. For my wife and me, this means that our visas are suspended; we […]

Looking for rigor in all the wrong places

My talk in the upcoming conference on Inference from Non Probability Samples, 16-17 Mar in Paris: Looking for rigor in all the wrong places What do the following ideas and practices have in common: unbiased estimation, statistical significance, insistence on random sampling, and avoidance of prior information? All have been embraced as ways of enforcing […]

Stan is hiring! hiring! hiring! hiring!

[insert picture of adorable cat entwined with Stan logo] We’re hiring postdocs to do Bayesian inference. We’re hiring programmers for Stan. We’re hiring a project manager. How many people we hire depends on what gets funded. But we’re hiring a few people for sure. We want the best best people who love to collaborate, who […]

To know the past, one must first know the future: The relevance of decision-based thinking to statistical analysis

We can break up any statistical problem into three steps: 1. Design and data collection. 2. Data analysis. 3. Decision making. It’s well known that step 1 typically requires some thought of steps 2 and 3: It is only when you have a sense of what you will do with your data, that you can […]

Time Inc. stoops to the level of the American Society of Human Genetics and PPNAS?

We fiddle while Rome burns: p-value edition

Raghu Parthasarathy presents a wonderfully clear example of disastrous p-value-based reasoning that he saw in a conference presentation. Here’s Raghu: Consider, for example, some tumorous cells that we can treat with drugs 1 and 2, either alone or in combination. We can make measurements of growth under our various drug treatment conditions. Suppose our measurements […]

“Which curve fitting model should I use?”

Oswaldo Melo writes: I have learned many of curve fitting models in the past, including their technical and mathematical details. Now I have been working on real-world problems and I face a great shortcoming: which method to use. As an example, I have to predict the demand of a product. I have a time series […]

Two unrelated topics in one post: (1) Teaching useful algebra classes, and (2) doing more careful psychological measurements

Kevin Lewis and Paul Alper send me so much material, I think they need their own blogs. In the meantime, I keep posting the stuff they send me, as part of my desperate effort to empty my inbox. 1. From Lewis: “Should Students Assessed as Needing Remedial Mathematics Take College-Level Quantitative Courses Instead? A Randomized […]

Sethi on Schelling

Interesting appreciation from an economist.

“Dirty Money: The Role of Moral History in Economic Judgments”

Recently in the sister blog . . . Arber Tasimi and his coauthor write: Although traditional economic models posit that money is fungible, psychological research abounds with examples that deviate from this assumption. Across eight experiments, we provide evidence that people construe physical currency as carrying traces of its moral history. In Experiments 1 and […]

Steve Fienberg

I did not know Steve Fienberg well, but I met him several times and encountered his work on various occasions, which makes sense considering his research area was statistical modeling as applied to social science. Fienberg’s most influential work must have been his books on the analysis of categorical data, work that was ahead of […]

On deck very soon

A bunch of the 170 are still in the queue. I haven’t been adding to the scheduled posts for awhile, instead I’ve been inserting topical items from time to time—I even got some vicious hate mail for my article on the electoral college—and then I’ve been shoving material for new posts into a big file […]

An efficiency argument for post-publication review

This came up in a discussion last week: We were talking about problems with the review process in scientific journals, and a commenter suggested that prepublication review should be more rigorous: There are lot of statistical missteps you just can’t catch until you actually have the replication data in front of you to work with […]

Hark, hark! the p-value at heaven’s gate sings

Three different people pointed me to this post, in which food researcher and business school professor Brian Wansink advises Ph.D. students to “never say no”: When a research idea comes up, check it out, put some time into it and you might get some success. I like that advice and I agree with it. Or, […]

Designing an animal-like brain: black-box “deep learning algorithms” to solve problems, with an (approximately) Bayesian “consciousness” or “executive functioning organ” that attempts to make sense of all these inferences

The journal Behavioral and Brain Sciences will be publishing this paper, “Building Machines That Learn and Think Like People,” by Brenden Lake, Tomer Ullman, Joshua Tenenbaum, and Samuel Gershman. Here’s the abstract: Recent progress in artificial intelligence (AI) has renewed interest in building systems that learn and think like people. Many advances have come from […]

The social world is (in many ways) continuous but people’s mental models of the world are Boolean

Raghu Parthasarathy points me to this post and writes: I wrote after seeing one too many talks in which someone bases boolean statements about effects “existing” or “not existing” (infuriating in itself) based on “p < 0.05” or “p > 0.5”. Of course, you’ve written tons of great things on the pitfalls, errors, and general […]

How to think about the p-value from a randomized test?

Roahn Wynart asks: Scenario: I collect a lot of data for a complex psychology experiment. I put all the raw data into a computer. I program the computer to do 100 statistical tests. I assign each statistical test to a key on my keyboard. However, I do NOT execute the statistical test. Each key will […]