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Archive of posts filed under the Teaching category.

The competing narratives of scientific revolution

Back when we were reading Karl Popper’s Logic of Scientific Discovery and Thomas Kuhn’s Structure of Scientific Revolutions, who would’ve thought that we’d be living through a scientific revolution ourselves? Scientific revolutions occur on all scales, but here let’s talk about some of the biggies: 1850-1950: Darwinian revolution in biology, changed how we think about […]

Amelia, it was just a false alarm

Nah, jet fuel can’t melt steel beams. I’ve watched enough conspiracy documentaries – Camp Cope Some ideas persist long after the mounting evidence against them becomes overwhelming. Some of these things are kooky but probably harmless (try as I might, I do not care about ESP etc), whereas some are deeply damaging (I’m looking at you “vaccines […]

What makes Robin Pemantle’s bag of tricks for teaching math so great?

It’s here, and he even calls it a “bag of tricks”! Robin’s suggestions are similar to what Deb and I recommend, but Robin’s article is a crisp 25 pages and is purely focused on general advice for getting things to go well in the classroom, whereas we spend most of our book on specific activities […]

Advice on soft skills for academics

Julia Hirschberg sent this along to the natural language processing mailing list at Columbia: here are some slides from last spring’s CRA-W Grad Cohort and previous years that might be of interest. all sorts of topics such as interviewing, building confidence, finding a thesis topic, preparing your thesis proposal, publishing, entrepreneurialism, and a very interesting […]

Of statistics class and judo class: Beyond the paradigm of sequential education

In judo class they kinda do the same thing every time: you warm up and then work on different moves. Different moves in different classes, and there are different levels, but within any level the classes don’t really have a sequence. You just start where you start, practice over and over, and gradually improve. Different […]

The statistical checklist: Could there be a list of guidelines to help analysts do better work?

[image of cat with a checklist] Paul Cuffe writes: Your idea of “researcher degrees of freedom” [actually not my idea; the phrase comes from Simmons, Nelson, and Simonsohn] really resonates with me: I’m continually surprised by how many researchers freestyle their way through a statistical analysis, using whatever tests, and presenting whatever results, strikes their […]

The “Carl Sagan effect”

Javier Benítez writes: I am not in academia, but I have learned a lot about science from what’s available to the public. But I also didn’t know that public outreach is looked down upon by academia. See the Carl Sagan Effect. Susana Martinez-Conde writes: One scientist, who agreed to participate on the condition of anonymity—an […]

He wants to know what to read and what software to learn, to increase his ability to think about quantitative methods in social science

A law student writes: I aspire to become a quantitatively equipped/focused legal academic. Despite majoring in economics at college, I feel insufficiently confident in my statistical literacy. Given your publicly available work on learning basic statistical programming, I thought I would reach out to you and ask for advice on understanding modeling and causal inference […]

He has a math/science background and wants to transition to social science. Should he get a statistics degree and do social science from there, or should he get a graduate degree in social science or policy?

Someone who graduated from college a couple years ago writes: My educational background is almost entirely science and math. However, since graduating and thinking about what I do, I’ve realized that I’ve always found demographics, geography, urban planning more interesting – and I’d like to pursue research in social science. I’m currently applying to MS […]

Data science teaching position in London

Seth Flaxman sends this along: The Department of Mathematics at Imperial College London wishes to appoint a Senior Strategic Teaching Fellow in Data Science, to be in post by September 2018 or as soon as possible thereafter. The role will involve developing and delivering a suite of new data science modules, initially for the MSc […]

Can somebody please untangle this one for us? Are centrists more, or less, supportive of democracy, compared to political extremists?

OK, this is a nice juicy problem for a political science student . . . Act 1: “Centrists Are the Most Hostile to Democracy, Not Extremists” David Adler writes in the New York Times: My research suggests that across Europe and North America, centrists are the least supportive of democracy, the least committed to its […]

How to read (in quantitative social science). And by implication, how to write.

I happened to come across this classic from 2014. For convenience I’ll just repeat it all here: It all started when I was reading Chris Blattman’s blog and noticed this: One of the most provocative and interesting field experiments I [Blattman] have seen in this year: Poor people often do not make investments, even when […]

There’s nothing embarrassing about self-citation

Someone sent me an email writing that one of my papers “has an embarrassing amount of self-citation.” I’m sorry that this person is embarrassed on my behalf. I’m not embarrassed at all. If I wrote something in the past that’s relevant, it makes sense to cite it rather than repeating myself, no? A citation is […]

Learn by experimenting!

A students wrote in one of his homework assignments: Sidenote: I know some people say you’re not supposed to use loops in R, but I’ve never been totally sure why this is (a speed thing?). My first computer language was Java, so my inclination is to think in loops before using some of the other […]

Mitzi’s talk on spatial models in Ann Arbor, Thursday 5 April 2018

Mitzi returns to her alma mater to give a talk at joint meeting of the Ann Arbor useR and ASA Meetups: Spatial models in Stan Abstract This case study shows how to efficiently encode and compute an intrinsic conditional autoregressive (ICAR) model in Stan. When data has a neighborhood structure, ICAR models provide spatial smoothing […]

Classical hypothesis testing is really really hard

This one surprised me. I included the following question in an exam: In causal inference, it is often important to study varying treatment effects: for example, a treatment could be more effective for men than for women, or for healthy than for unhealthy patients. Suppose a study is designed to have 80% power to detect […]

What to teach in a statistics course for journalists?

Pascal Biber writes: I am a science journalist for Swiss public television and have previously regularly covered the “crisis in science” on Swiss public radio, including things like p-hacking, relative risks, confidence intervals, reproducibility etc. I have been giving courses in basic statistics and how to read scientific studies for Swiss journalists without science backgrounds. […]

“revision-female-named-hurricanes-are-most-likely-not-deadlier-than-male-hurricanes”

Gary Smith sends along this news article from Jason Samenow, weather editor of the Washington Post, who writes: Three years ago, a scientific study claimed that storms named Debby are predisposed to kill more people than storms named Don. The study alleged that people don’t take female-named storms as seriously. Numerous analyses have since found […]

New Stan case studies: NNGP and Lotka-Volterra

It’s only January and we already have two new case studies up on the Stan site. Two new case studies Lu Zhang of UCLA contributed a case study on nearest neighbor Gaussian processes. Bob Carpenter (that’s me!) of Columbia Uni contributed one on Lotka-Volterra population dynamics. Mitzi Morris of Columbia Uni has been updating her […]

“The following needs to be an immutable law of journalism: when someone with no track record comes into a field claiming to be able to do a job many times better for a fraction of the cost, the burden of proof needs to shift quickly and decisively onto the one making the claim. The reporter simply has to assume the claim is false until substantial evidence is presented to the contrary.”

Mark Palko writes: The following needs to be an immutable law of journalism: when someone with no track record comes into a field claiming to be able to do a job many times better for a fraction of the cost, the burden of proof needs to shift quickly and decisively onto the one making the […]