Category: Statistics

Prior distributions for covariance matrices

Someone sent me a question regarding the inverse-Wishart prior distribution for covariance matrix, as it is the default in some software he was using. Inverse-Wishart does not make sense for prior distribution; it has problems because the shape and scale are tangled. See this paper, “Visualizing Distributions of Covariance Matrices,” by Tomoki Tokuda, Ben Goodrich, […]

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Should we be concerned about MRP estimates being used in later analyses? Maybe. I recommend checking using fake-data simulation.

Someone sent in a question (see below). I asked if I could post the question and my reply on blog, and the person responded: Absolutely, but please withhold my name because this is becoming a touchy issue within my department. The boldface was in the original. I get this a lot. There seems to be […]

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My footnote about global warming

At the beginning of my article, How to think scientifically about scientists’ proposals for fixing science, which we discussed yesterday, I wrote: Science is in crisis. Any doubt about this status has surely been been dispelled by the loud assurances to the contrary by various authority figures who are deeply invested in the current system […]

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Memento & Quiz (on SEV): Excursion 3, Tour I.

As you enjoy the weekend discussion & concert in the Captain’s Central Limit Library & Lounge, your Tour Guide has prepared a brief overview of Excursion 3 Tour I, and a short (non-severe) quiz on severity, based on exhibit (i).* We move from Popper through a gallery on “Data Analysis in the 1919 Eclipse tests […]

A parable regarding changing standards on the presentation of statistical evidence

Now, the P-value Sneetches Had tables with stars. The Bayesian Sneetches Had none upon thars. Those stars weren’t so big. They were really so small. You might think such a thing wouldn’t matter at all. But, because they had stars, all the P-value Sneetches Would brag, “We’re the best kind of Sneetch on the Beaches. […]

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Niall Ferguson and the perils of playing to your audience

History professor Niall Ferguson had another case of the sillies. Back in 2012, in response to Stephen Marche’s suggestion that Ferguson was serving up political hackery because “he has to please corporations and high-net-worth individuals, the people who can pay 50 to 75K to hear him talk,” I wrote: But I don’t think it’s just […]

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“Statistical insights into public opinion and politics” (my talk for the Columbia Data Science Society this Wed 9pm)

7pm in Fayerweather 310: Why is it more rational to vote than to answer surveys (but it used to be the other way around)? How does this explain why we should stop overreacting to swings in the polls? How does modern polling work? What are the factors that predict election outcomes? What’s good and bad […]

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Bayes, statistics, and reproducibility: “Many serious problems with statistics in practice arise from Bayesian inference that is not Bayesian enough, or frequentist evaluation that is not frequentist enough, in both cases using replication distributions that do not make scientific sense or do not reflect the actual procedures being performed on the data.”

This is an abstract I wrote for a talk I didn’t end up giving. (The conference conflicted with something else I had to do that week.) But I thought it might interest some of you, so here it is: Bayes, statistics, and reproducibility The two central ideas in the foundations of statistics—Bayesian inference and frequentist […]

The post Bayes, statistics, and reproducibility: “Many serious problems with statistics in practice arise from Bayesian inference that is not Bayesian enough, or frequentist evaluation that is not frequentist enough, in both cases using replication distributions that do not make scientific sense or do not reflect the actual procedures being performed on the data.” appeared first on Statistical Modeling, Causal Inference, and Social Science.