Paul Ginsparg and I were discussing that mortality rate adjustment example. I pointed him to this old tutorial that laid out the age adjustment step by step, and he sent along this: For mortality rate junkies, here’s another example [by Steven Martin and Laudan Aron] of bundled stats lending to misinterpretation, in this case not […]

**Teaching**category.

## Trial by combat, law school style

This story is hilarious. 78-year-old law professor was told he can no longer teach a certain required course; this jeopardizes his current arrangement where he is paid full time but only teaches one semester a year, so he’s suing his employer . . . Columbia Law School. The beautiful part of this story is how […]

## Self-study resources for Bayes and Stan?

Someone writes: I’m interested in learning more about data analysis techniques; I’ve bought books on Bayesian Statistics (including yours), on R programming, and on several other ‘related stuff’. Since I generally study this whenever I have some free time, I’m looking for sources that are meant for self study. Are there any sources that you […]

## Nice interface, poor content

Jim Windle writes: This might interest you if you haven’t seen it, and I don’t think you’ve blogged about it. I’ve only checked out a bit of the content but it seems a pretty good explanation of basic statistical concepts using some nice graphics. My reply: Nice interface, but their 3 topics of Statistical Inference […]

## Also holding back progress are those who make mistakes and then label correct arguments as “nonsensical.”

Here’s James Heckman in 2013: Also holding back progress are those who claim that Perry and ABC are experiments with samples too small to accurately predict widespread impact and return on investment. This is a nonsensical argument. Their relatively small sample sizes actually speak for — not against — the strength of their findings. Dramatic […]

## What readings should be included in a seminar on the philosophy of statistics, the replication crisis, causation, etc.?

André Ariew writes: I’m a philosopher of science at the University of Missouri. I’m interested in leading a seminar on a variety of current topics with philosophical value, including problems with significance tests, the replication crisis, causation, correlation, randomized trials, etc. I’m hoping that you can point me in a good direction for accessible readings […]

## It’s hard to know what to say about an observational comparison that doesn’t control for key differences between treatment and control groups, chili pepper edition

Jonathan Falk points to this article and writes: Thoughts? I would have liked to have seen the data matched on age, rather than simply using age in a Cox regression, since I suspect that’s what really going on here. The non-chili eaters were much older, and I suspect that the failure to interact age, or […]

## Seemingly intuitive and low math intros to Bayes never seem to deliver as hoped: Why?

This post was prompted by recent nicely done videos by Rasmus Baath that provide an intuitive and low math introduction to Bayesian material. Now, I do not know that these have delivered less than he hoped for. Nor I have asked him. However, given similar material I and others have tried out in the past that […]

## Giving feedback indirectly by invoking a hypothetical reviewer

Ethan Bolker points us to this discussion on “How can I avoid being “the negative one” when giving feedback on statistics?”, which begins: Results get sent around a group of biological collaborators for feedback. Comments come back from the senior members of the group about the implications of the results, possible extensions, etc. I look […]

## Animating a spinner using ggplot2 and ImageMagick

It’s Sunday, and I [Bob] am just sitting on the couch peacefully ggplotting to illustrate basic sample spaces using spinners (a trick I’m borrowing from Jim Albert’s book Curve Ball). There’s an underlying continuous outcome (i.e., where the spinner lands) and a quantization into a number of regions to produce a discrete outcome (e.g., “success” […]

## No, I’m not blocking you or deleting your comments!

Someone wrote in: I am worried you may have blocked me from commenting on your blog (because a couple of comments I made aren’t there). . . . Or maybe I failed to post correctly or maybe you just didn’t think my comments were interesting enough. . . . This comes up from time to […]

## Bad Numbers: Media-savvy Ivy League prof publishes textbook with a corrupted dataset

[cat picture] I might not have noticed this one, except that it happened to involve Congressional elections, and this is an area I know something about. The story goes like this. I’m working to finish up Regression and Other Stories, going through the examples. There’s one where we fit a model to predict the 1988 […]

## Kaiser Fung’s data analysis bootcamp

Kaiser Fung announces a new educational venture he’s created, a bootcamp (12-week full-time in-person program with a curriculum) of short courses with a goal of getting people their first job in an analytics role for a business unit (not engineering or software development, so he is not competing directly with MS Data Science or data […]

## Hey—here are some tips on communicating data and statistics!

This fall I’ll be again teaching the course, Communicating Data and Statistics. Here’s the rough course plan. I’ll tinker with it between now and September but this is the basic idea. (The course listing is here, but that online description is out of date; the course plan linked above is more accurate.) Here are the […]

## Taking Data Journalism Seriously

This is a bit of a followup to our recent review of “Everybody Lies.” While writing the review I searched the blog for mentions of Seth Stephens-Davidowitz, and I came across this post from last year, concerning a claim made by author J. D. Vance that “the middle part of America is more religious than […]

## Should computer programming be a prerequisite for learning statistics?

[cat picture] This came up in a recent discussion thread, I can’t remember exactly where. A commenter pointed out, correctly, that you shouldn’t require computer programming as a prerequisite for a statistics course: there’s lots in statistics that can be learned without knowing how to program. Sure, if you can program you can do a […]

## “P-hacking” and the intention-to-cheat effect

I’m a big fan of the work of Uri Simonsohn and his collaborators, but I don’t like the term “p-hacking” because it can be taken to imply an intention to cheat. The image of p-hacking is of a researcher trying test after test on the data until reaching the magic “p less than .05.” But, […]

## Stan without frontiers, Bayes without tears

[cat picture] This recent comment thread reminds me of a question that comes up from time to time, which is how to teach Bayesian statistics to students who aren’t comfortable with calculus. For continuous models, probabilities are integrals. And in just about every example except the one at 47:16 of this video, there are multiple […]

## Teaching Statistics: A Bag of Tricks (second edition)

Hey! Deb Nolan and I finished the second edition of our book, Teaching Statistics: A Bag of Tricks. You can pre-order it here. I love love love this book. As William Goldman would say, it’s the “good parts version”: all the fun stuff without the standard boring examples (counting colors of M&M’s, etc.). Great stuff […]

## Mmore from Ppnas

Kevin Lewis asks for my take on two new papers: Study 1: Honesty plays a key role in social and economic interactions and is crucial for societal functioning. However, breaches of honesty are pervasive and cause significant societal and economic problems that can affect entire nations. Despite its importance, remarkably little is known about the […]