This post is by Bob. I have no idea what Andrew will make of these graphs; I’ve been hoping to gather enough comments from him to code up a ggplot theme. Shravan, you can move along, there’s nothing here but baseball. Jim Albert created some great graphs for strike-count performance in a series of two […]

**Teaching**category.

## Happy talk, meet the Edlin factor

Mark Palko points us to this op-ed in which psychiatrist Richard Friedman writes: There are also easy and powerful ways to enhance learning in young people. For example, there is intriguing evidence that the attitude that young people have about their own intelligence — and what their teachers believe — can have a big impact […]

## Statistics is like basketball, or knitting

I had a recent exchange with a news reporter regarding one of those silly psychology studies. I took a look at the article in question—this time it wasn’t published in Psychological Science or PPNAS so it didn’t get saturation publicity—and indeed it was bad, laughably bad. They didn’t just have the garden of forking paths, […]

## He wants to teach himself some statistics

Milan Griffes writes: I work at GiveWell, which you’ve kindly written about in the past. I wanted to ask for your current thoughts on the best way to learn statistics outside of formal education since it’s been a few years since your last post on this topic. Do you have any advice for someone with […]

## Graphical Data Analysis with R

Graphical Data Analysis with R: that’s the title of Antony Unwin’s new book. Here are the chapter titles: Ch01 Setting the Scene Ch03 Examining continuous variables Ch04 Displaying Categorial Data Ch05 Looking for Structure Ch06 Investigating Multivariate Continuous Data Ch07 Studying Multivariate Categorical Data Ch08 Getting an Overview Ch09 Graphics and Data Quality Ch10 Comparisons […]

## “What is Bayesian data analysis? Some examples”: My lecture at the New School this Wed noon

What is Bayesian data analysis? Some examples This is for their econ program, I think? I’ll demonstrate the three stages of Bayesian data analysis, going over examples such as the world cup analysis, the monster study, spell checking, the so-called global climate challenge, trends in death rates, . . . we’ll see how much time […]

## Stat Podcast Plan

In my course on Statistical Communication and Graphics, each class had a special guest star who would answer questions on his or her area of expertise. These were not “guest lectures”—there were specific things I wanted the students to learn in this course, it wasn’t the kind of seminar where they just kick back each […]

## My namesake doesn’t seem to understand the principles of decision analysis

It says “Never miss another deadline.” But if you really could never miss your deadlines, you’d just set your deadlines earlier, no? It’s statics vs. dynamics all over again. That said, this advice seems reasonable: The author has also developed a foolproof method of structuring your writing, so that you make effective use of your […]

## McElreath’s *Statistical Rethinking: A Bayesian Course with Examples in R and Stan *

We’re not even halfway through with January, but the new year’s already rung in a new book with lots of Stan content: Richard McElreath (2016) Statistical Rethinking: A Bayesian Course with Examples in R and Stan. Chapman & Hall/CRC Press. This one got a thumbs up from the Stan team members who’ve read it, and […]

## Street-Fighting Probability and Street-Fighting Stats: 2 One-Week Modules

In a comment to my previous post on the Street-Fighting Math course, Alex wrote: Have you thought about incorporating this material into more conventional classes? I can see this being very good material for a “principles” section of a linear modeling or other applied statistics course. It could give students a sense for how to […]

## New course: Street-Fighting Math

I want to teach a course next year based on two books by Sanjoy Mahajan: Street-Fighting Mathematics and The Art of Insight in Science and Engineering. You can think of the two books as baby versions of Weisskopf’s 1969 classic, Modern Physics from an Elementary Point of View. Another book in the same vein is […]

## Guess what today’s kids are clicking on: My presentation at the Electronic Conference on Teaching Statistics

Changing everything at once: Student-centered Learning, computerized practice exercises, evaluation of student progress, and a modern syllabus to create a completely new introductory statistics course Andrew Gelman, Department of Statistics, Columbia University It should be possible to improve the much-despised introductory statistics course in several ways: (1) altering the classroom experience toward active learning, (2) […]

## You’ll never believe what this girl wrote in her diary (NSFW)

Arber Tasimi heard about our statistics diaries and decided to try it out in the psychology class he was teaching. The students liked his class but a couple of them pushed back against the diaries, describing the assignment as pointless or unhelpful in their learning. This made me think that it may be that a […]

## First, second, and third order bias corrections (also, my ugly R code for the mortality-rate graphs!)

As an applied statistician, I don’t do a lot of heavy math. I did prove a true theorem once (with the help of some collaborators), but that was nearly twenty years ago. Most of the time I walk along pretty familiar paths, just hoping that other people will do the mathematical work necessary for me […]

## You won’t believe these stunning transformations: How to parameterize hyperpriors in hierarchical models?

Isaac Armstrong writes: I was working through your textbook “Data Analysis Using Regression and Multilevel/Hierarchical Models” but wanted to learn more and started working through your “Bayesian Data Analysis” text. I’ve got a few questions about your rat tumor example that I’d like to ask. I’ve been trying to understand one of the hierarchical models […]

## Don’t miss this one: “Modern Physics from an Elementary Point of View”

I was googling *back of the envelope* for a recent post and I came across these lecture notes by Victor Weisskopf from 1969. I can no longer really follow this sort of thing—I really really wish this had been my textbook back when I was studying physics. If they’d taught us this stuff, I might’ve […]

## 3 postdoc opportunities you can’t miss—here in our group at Columbia! Apply NOW, don’t miss out!

Hey, just once, the Buzzfeed-style hype is appropriate. We have 3 amazing postdoc opportunities here, and you need to apply NOW. Here’s the deal: we’re working on some amazing projects. You know about Stan and associated exciting projects in computational statistics. There’s the virtual database query, which is the way I like to describe our […]

## Click here to get FREE tix to my webinar with Brad Efron this Wednesday!

The Royal Statistical Society (U.K.) has organized a discussion of a new paper, Frequentist accuracy of Bayesian estimates, by Brad Efron. The discussion will be an online event (a “webinar”) on 21 Oct 2015 (that’s right, “Back to the Future Day”) at noon 11am eastern time (4pm in the U.K.). Brad will present, I’ll ask […]