Skip to content
Archive of posts filed under the Teaching category.

We got mooks

Columbia University’s Data Science Institute is releasing some mooks, and I’m part of it. I’ll first give the official announcement and then share some of my thoughts. The official announcement: The Data Science Institute at Columbia University is excited to announce the launch of its first online-education series, Data Science and Analytics in Context, on […]

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 […]

Benford lays down the Law

A few months ago I received in the mail a book called An Introduction to Benford’s Law by Arno Berger and Theodore Hill. I eagerly opened it but I lost interest once I realized it was essentially a pure math book. Not that there’s anything wrong with math, it just wasn’t what I wanted to […]

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 […]

Anti-cheating robots

Paul Alper writes: Surely you would like to comment on the amazing escalation in the anti-cheating tech world. I predict it will be followed by some clever software which makes it appear that the student enrolled is actually the one taking the exam. Reminiscent of the height of the cold war of counter weapons and […]

Syllabus for my course on Communicating Data and Statistics

Actually the course is called Statistical Communication and Graphics, but I was griping about how few students were taking the class, and someone suggested the title Communicating Data and Statistics as being a bit more appealing. So I’ll go with that for now. I love love love this class and everything that’s come from it […]

Stan Puzzle #1: Inferring Ability from Streaks

Inspired by X’s blog’s Le Monde puzzle entries, I have a little Stan coding puzzle for everyone (though you can solve the probabilty part of the coding problem without actually knowing Stan). This almost (heavy emphasis on “almost” there) makes me wish I was writing exams. Puzzle #1: Inferring Ability from Streaks Suppose a player […]

What was the worst statistical communication experience you’ve ever had?

In one of the jitts for our statistical communication class we asked, “What was the worst statistical communication experience you’ve ever had?” And here were the responses (which I’m sharing with permission from the students): Not sure if this counts, but I used to work with a public health researcher who published a journal article […]

Matlab/Octave and Python demos for BDA3

My Bayesian Data Analysis course at Aalto University started today with a record number of 84 registered students! In my course I have used some Matlab/Octave demos for several years. This summer Tuomas Sivula translated most of them to Python and Python notebook. Both Matlab/Octave and Python demos are now available at Github in hope they […]

A political sociological course on statistics for high school students

Ben Frisch writes: I am designing a semester long non-AP Statistics course for high school juniors and seniors. I am wondering if you had some advice for the design of my class. My currentthinking for the design of the class includes: 0) Brief introduction to R/ R Studio and descriptive statistics and data sheet structure. […]

Data-analysis assignments for BDA class?

In my Bayesian data analysis class this fall, I’m planning on doing some lecturing and class discussion, but the core of the course will be weekly data-analysis assignments where they do applied statistics using Stan (to fit models) and R (to pre-process the data and post-process the inferences). So, I need a bunch of examples. […]

My 2 classes this fall

Stat 6103, Bayesian Data Analysis Modern Bayesian methods offer an amazing toolbox for solving science and engineering problems. We will go through the book Bayesian Data Analysis and do applied statistical modeling using Stan, using R (or Python or Julia if you prefer) to preprocess the data and postprocess the analysis. We will also discuss […]

Neither time nor stomach

Mark Palko writes: Thought you might be interested in an EngageNY lesson plan for statistics. So far no (-2)x(-2) = -4 (based on a quick read), but still kind of weak. It bothers me that they keep talking about randomization but only for order of test; they assigned treatment A to the first ten of […]

Stan Meetup Talk in Ann Arbor this Wednesday (5 Aug 2015)

I (Bob) will be presenting an overview of (R)Stan at the Ann Arbor R User Group meetup this Wednesday night (5 August 2015) at 7 PM. To see the abstract and register to attend: RStan: Statistical Modeling Made Easy with Bob Carpenter Wednesday, Aug 5, 2015, 7:00 PM Barracuda Networks317 Maynard St Ann Arbor, MI […]

Statistical/methodological prep for a career in neuroscience research?

Shea Levy writes: I’m currently a software developer, but I’m trying to transition to the neuroscience research world. Do you have any general advice or recommended resources to prepare me to perform sound and useful experimental design and analyses? I have a very basic stats background from undergrad plus eclectic bits and pieces I’ve picked […]

What’s the stupidest thing the NYC Department of Education and Columbia University Teachers College did in the past decade?

Ummm, how bout this: The principal of a popular elementary school in Harlem acknowledged that she forged answers on students’ state English exams in April because the students had not finished the tests . . . As a result of the cheating, the city invalidated several dozen English test results for the school’s third grade. […]