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Archive of posts filed under the Teaching category.

Bad Statistics: Ignore or Call Out?

Evelyn Lamb adds to the conversation that Jeff Leek and I had a few months ago. It’s a topic that’s worth returning to, in light of our continuing discussions regarding the crisis of criticism in science.

Some quick disorganzed tips on classroom teaching

Below are a bunch of little things I typically mention at some point when I’m teaching my class on how to teach. But my new approach is to minimize lecturing, and certainly not to waste students’ time by standing in front of a group of them, telling them things they could’ve read at their own […]

My courses this fall at Columbia

Stat 6103, Bayesian Data Analysis, TuTh 1-2:30 in room 428 Pupin Hall: We’ll be going through the book, section by section. Follow the link to see slides and lecture notes from when I taught this course a couple years ago. This course has a serious workload: each week we have three homework problems, one theoretical, […]

Luck vs. skill in poker

The thread of our recent discussion of quantifying luck vs. skill in sports turned to poker, motivating the present post. 1. Can good poker players really “read” my cards and figure out what’s in my hand? For a couple years in grad school a group of us had a regular Thursday-night poker game, nickel-dime-quarter with […]

Skepticism about a published claim regarding income inequality and happiness

Frank de Libero writes: I read your Chance article (disproving that no one reads Chance!) re communicating about flawed psychological research. And I know from your other writings of your continuing good fight against misleading quantitative work. I think you and your students might be interested on my recent critique of a 2011 paper published […]

Stan World Cup update

The other day I fit a simple model to estimate team abilities from World Cup outcomes. I fit the model to the signed square roots of the score differentials, using the square root on the theory that when the game is less close, it becomes more variable. 0. Background As you might recall, the estimated […]

Stan London Meetup 16 July

Michael Betancourt announces: The Stan Development Team is happy to announce the first Stan London Meetup, Wednesday, July 16th, 6-8 PM Bentham House, Seminar Room 4 4-8 Endsleigh Gardens, London, WC1H 0EG Nominally the plan is to begin with a casual introduction to Stan and then break out into discussion based on the interests of […]

Stan hands-on introduction in NYC Tues 24 Jun 7pm

Ben Goodrich, one of the Stan developers, will be leading the session. Bring a laptop, if that’s what you’re working on. We’ll cover: • installation of CmdStan, RStan, and possibly PyStan (if we can find an expert) • work through parts of the Stan language through a few models Signup information is here. Anyone who’s […]

Hurricanes/himmicanes extra: Again with the problematic nature of the scientific publication process

Jeremy Freese has the story. To me, the sad thing is not that people who don’t understand statistics are doing research. After all, statistics is hard, and to require statistical understanding of all quantitative researchers would be impossible to enforce in any case. Indeed, if anything, one of the goals of the statistical profession is […]

He’s not so great in math but wants to do statistics and machine learning

I received the following email from someone who wishes to remain anonymous: I am a longtime reader of your blog and it, along with other factors that I will explain briefly, has motivated to pursue a second masters degree in statistics and machine learning. The problem is, my math isn’t great. I understand statistics and […]