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Macartan Humphreys supplied this amusing demo. Just click on the link and try it—it’s fun! Here’s an example: I came up with 10 random numbers: > round(.5+runif(10)*100) [1] 56 23 70 83 29 74 23 91 25 89 and entered them into Macartan’s app, which promptly responded: Unbelievable! You chose the numbers 56 23 70 […]
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A couple years ago I gave a talk at West Point. It was fun. The students are all undergraduates, and most of the instructors were just doing the job for two years or so between other assignments. The permanent faculty were focused on teaching and organizing the curriculum. As part of my visit I sat […]
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I’d like to see a Stan implementation of the analysis presented in this comment by Gary from a year and a half ago.
The post Free Stan T-shirt to the first “little twerp” who does a (good) Bayesian analysis of Jon Lee Anderson’s height appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Tom Scocca files a bizarrely sane column summarizing the famous shortstop’s accomplishments: Derek Jeter was an OK ballplayer. He was pretty good at playing baseball, overall, and he did it for a pretty long time. . . . You have to be good at baseball to last 20 seasons in the major leagues. . . […]
The post “Derek Jeter was OK” appeared first on Statistical Modeling, Causal Inference, and Social Science.

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Helen Steingroever writes: I’m currently working on a model comparison paper using WAIC, and would like to ask you the following question about the WAIC computation: I have data of one participant that consist of 100 sequential choices (you can think of these data as being a time series). I want to compute the WAIC […]
The post Waic for time series appeared first on Statistical Modeling, Causal Inference, and Social Science.