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Archive of posts filed under the Teaching category.

Short course on Bayesian data analysis and Stan 19-21 July in NYC!

Bob Carpenter, Daniel Lee, and I are giving a 3-day short course in two weeks. Before class everyone should install R, RStudio and RStan on their computers. If problems occur please join the stan-users group and post any questions. It’s important that all participants get Stan running and bring their laptops to the course. Class […]

God is in every leaf of every probability puzzle

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. […]

Because there is no observable certainty other than the existence of thought

Someone who is teaching a college philosophy class writes: We discussed Descartes’ Meditations on First Philosophy last week — specifically, concerning the existence of God — and I had students write down their best proof for God’s existence in one minute, independent of their beliefs. Attached is a particularly funny response: Another good one was […]

Applied regression and multilevel modeling books using Stan

Edo Navot writes: Are there any plans in the works to update your book with Prof. Hill on hierarchical models to a new edition with example code in Stan? Yes, we are planning to break it up into 2 books and do all the modeling for both books in Stan. It’s waiting on some new […]

We need a title for our Daily Beast column

Kaiser and I will soon start a weekly column for the Daily Beast, focusing on statistics that are cited in political and civic debates. The question is, what to call it? We have a few possibilities but aren’t thrilled with any of them. So we could use some help from the wisdom of the crowd. […]

In criticism of criticism of criticism

I do a lot of criticism. I’m sure you can think of lots of things that I like to criticize, but to keep things simple, let’s focus on graphics criticism, for example this post where I criticized a graph for false parallelism. At this point some people would say that graphics criticism is mean, and […]

He’s looking for probability puzzles

Adrian Torchiana writes: I recently created a little probability puzzle app for android, and I was wondering whether you have any suggestions for puzzles that are engaging, approachable to someone who hasn’t taken a probability course, and don’t involve coins or dice. I think my easy puzzles are easy enough, but I’m having trouble thinking […]

Which of these classes should he take?

Jake Humphries writes: I for many years wanted to pursue medicine but after recently completing a master of public health, I caught the statistics bug. I need to complete the usual minimum prerequisites for graduate study in statistics (calculus through multivariable calculus plus linear algebra) but want to take additional math courses as highly competitive […]

Why do we communicate probability calculations so poorly, even when we know how to do it better?

Haynes Goddard writes: I thought to do some reading in psychology on why Bayesian probability seems so counterintuitive, and making it difficult for many to learn and apply. Indeed, that is the finding of considerable research in psychology. It turns out that it is counterintuitive because of the way it is presented, following no doubt […]

How can teachers of (large) online classes use text data from online learners?

Dustin Tingley sends along a recent paper (coauthored with Justin Reich, Jetson Leder-Luis, Margaret Roberts, and Brandon Stewart), which begins: Dealing with the vast quantities of text that students generate in a Massive Open Online Course (MOOC) is a daunting challenge. Computational tools are needed to help instructional teams uncover themes and patterns as MOOC […]

A rare topical post

Harvey Motulsky writes: Every year at passover, I struggle to peel two dozen hard boiled eggs and search the web to see if there isn’t a trick to do it better. But all the hits say the same thing: put the eggs in cold water, then bring to a boil. But this guy [J. Kenji […]

Time-release pedagogy??

Mark Palko points to this report and writes: Putting aside my concerns with the “additional years of learning” metric (and I have a lot of them), I have the feeling that there’s something strange here or i’m missing something obvious. That jump from 3-year impact to 4-year seems excessive. The press release links to a […]

Regression: What’s it all about? [Bayesian and otherwise]

Regression: What’s it all about? Regression plays three different roles in applied statistics: 1. A specification of the conditional expectation of y given x; 2. A generative model of the world; 3. A method for adjusting data to generalize from sample to population, or to perform causal inferences. We could also include prediction, but I […]

Define first, prove later

This post by John Cook features a quote form a book “Calculus on Manifolds,” by Michael Spivak which I think was the textbook for a course I took in college where we learned how to prove Stokes’s theorem, which is something in multivariable calculus involving the divergence and that thing that you get where you […]

New time unit needed!

We need a time unit that’s bigger than a minute but smaller than an hour. I thought of it when writing this comment in which I referred to “2100 valuable minutes of classroom time” during the semester (that’s 75 minutes per class, twice a week, for 14 weeks). A minute of class time is pretty […]

Stock-and-flow and other concepts that are important in statistical modeling but typically don’t get taught to statisticians

Bill Harris writes: You’ve written about causality somewhat often, and you, along with perhaps everyone who has done anything with statistics, have written that “correlation is not causation.” When you say that correlation is not causation, you seem to be pointing out cases where correlation exists but causality does not. While that’s important, there’s another […]

“A small but growing collection of studies suggest X” . . . huh?

Lee Beck writes: I’m curious if you have any thoughts on the statistical meaning of sentences like “a small but growing collection of studies suggest [X].” That exact wording comes from this piece in the New Yorker, but I think it’s the sort of expression you often see in science journalism (“small but mounting”, “small […]

“Academics should be made accountable for exaggerations in press releases about their own work”

Fernando Martel Garcia points me to this news article by Ben Goldacre: For anyone with medical training, mainstream media coverage of science can be an uncomfortable read. It is common to find correlational findings misrepresented as denoting causation, for example, or findings in animal studies confidently exaggerated to make claims about treatment for humans. But […]

Statistical Significance – Significant Problem?

John Carlin, who’s collaborated on some of my recent work on Type S and Type M errors, prepared this presentation for a clinical audience. It might be of interest to some of you. The ideas and some of the examples should be familiar to regular readers of this blog, but it could be useful to […]

“Peer assessment enhances student learning”

Dennis Sun, Naftali Harris, Guenther Walther, and Michael Baiocchi write: Peer assessment has received attention lately as a way of providing personalized feedback that scales to large classes. . . . By conducting a randomized controlled trial in an introductory statistics class, we provide evidence that peer assessment causes significant gains in student achievement. The […]