Last week I gave a talk in the Yahoo! Big Thinkers series. The video of the talk is now online and embedded below.

Thanks to Robert Grant, we now have a Stata interface! For more details, see: Robert Grant’s Blog: Introducing StataStan Jonah and Ben have already kicked the tires, and it works. We’ll be working on it more as time goes on as part of our Institute of Education Sciences grant (turns out education researchers use […] The post Introducing StataStan appeared first on Statistical Modeling, Causal Inference, and Social Science.

Radford shared with us this probability puzzle of his from 1999: A couple you’ve just met invite you over to dinner, saying “come by around 5pm, and we can talk for a while before our three kids come home from school at 6pm”. You arrive at the appointed time, and are invited into the house. […] The post God is in every leaf of every probability puzzle appeared first on…

Mon: God is in every leaf of every probability puzzle Tues: Where does Mister P draw the line? Wed: Recently in the sister blog Thurs: Humility needed in decision-making Fri: “Why should anyone believe that? Why does it make sense to model a series of astronomical events as though they were spins of a roulette […] The post On deck this week appeared first on Statistical Modeling, Causal Inference, and…

When I am computing with SAS/IML matrices and vectors, I often want to label the columns or rows so that I can better understand the data. The labels are called headers, and the COLNAME= and ROWNAME= options in the SAS/IML PRINT statement enable you to add headers for columns and […] The post An easy way to use numbers for column headers appeared first on The DO Loop.

Gelman sums up the reasons why there is a crisis in experimental research in our time. The journal publication process fails to catch fake research (let alone bad research), and the new media prefer sensationalist headlines over good science. Many res...

Our first Daily Beast column is here. The post What’s So Fun About Fake Data? appeared first on Statistical Modeling, Causal Inference, and Social Science.

Nathan Lemoine writes: I’m an ecologist, and I typically work with small sample sizes from field experiments, which have highly variable data. I analyze almost all of my data now using hierarchical models, but I’ve been wondering about my interpretation of the posterior distributions. I’ve read your blog, several of your papers (Gelman and Weakliem, […] The post Interpreting posterior probabilities in the context of weakly informative priors appeared first…

Eric Tassone writes: So, here’s a Bill James profile from late-ish 2014 that I’d missed until now. It’s baseball focused, which was nice — so many recent articles about him are non-baseball stuff. Here’s an extended excerpt of a part I found refreshing, though it’s probably just that my expectations have gotten pretty low of […] The post “Faith means belief in something concerning which doubt is theoretically possible.” —…

Win-Vector LLC is a consultancy founded in 2007 that specializes in research, algorithms, data-science, and training. (The name is an attempt at a mathematical pun.) Win-Vector LLC can complete your high value project quickly (some examples), and train...

Psychologists speak of “folk psychology” or “folk physics” as the intuitive notions we have about the world, which typically describe some aspects of reality but ultimately are gross oversimplifications. I encountered a good example of “folk genetics” the other day after following the clickbait link to “22 Things We Learned Hanging Out With Sam Smith”: […] The post Sam Smith sings like a dream but he’s as clueless as Nicholas…

Here are the download figures for my e-book with George as sent to me last week by my publisher Springer-Verlag. With an interesting surge in the past year. Maybe simply due to new selling strategies of the published rather to a wider interest in the book. (My royalties have certainly not increased!) Anyway thanks to […]

If it's somethin' weird an' it don't look good, who ya gonna call? Statbusters! That is the name of our weekly column for the Daily Beast, starting today. Andrew Gelman and I will alternate weeks. As I write this, nothing is up yet. Try going to the Daily Beast to find Andrew's first column.

Last tuesday, at the annual meeting of the French Economic Association, I was having lunch with Alfred, and while we were chatting about modeling issues (econometric models against machine learning prediction), he asked me what boosting was. Since I could not be very specific, we’ve been looking at wikipedia webpage. Boosting is a machine learning ensemble meta-algorithm for reducing bias primarily and also variance in supervised learning, and a family of machine learning algorithms…

Consider 2 random variables, and , from the normal distribution , where is unknown. Then the statistic has the distribution . The distribution of does not depend on , so is an ancillary statistic for . Note that, if is unknown, then is not ancillary for .Filed under: Mathematical Statistics, Statistics, Statistics Lesson of the […]

Kaiser Fung and I have a new weekly column for the Daily Beast. After much deliberation, we gave it the title Statbusters (the runner-up choice was Dirty Data; my personal preference was Statboyz in the Hood, but, hey, who ever listens to me on anything?). The column will appear every Saturday, and Kaiser and I […] The post Our new column in the Daily Beast appeared first on Statistical Modeling,…