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

“Here’s an interesting story right in your sweet spot”

Jonathan Falk writes: Here’s an interesting story right in your sweet spot: Large effects from something whose possible effects couldn’t be that large? Check. Finding something in a sample of 1024 people that requires 34,000 to gain adequate power? Check. Misuse of p values? Check Science journalist hype? Check Searching for the cause of an […]

The status-reversal heuristic

Awhile ago we came up with the time-reversal heuristic, which was a reaction to the common situation that there’s a noisy study, followed by an unsuccessful replication, but all sorts of people want to take the original claim as the baseline and construct high walls to make it difficult to move away from that claim. […]

How to think scientifically about scientists’ proposals for fixing science

I kinda like this little article which I wrote a couple years ago while on the train from the airport. It will appear in the journal Socius. Here’s how it begins: Science is in crisis. Any doubt about this status has surely been been dispelled by the loud assurances to the contrary by various authority […]

Rachel Tanur Memorial Prize for Visual Sociology

Judith Tanur writes: The Rachel Tanur Memorial Prize for Visual Sociology recognizes students in the social sciences who incorporate visual analysis in their work. The contest is open worldwide to undergraduate and graduate students (majoring in any social science). It is named for Rachel Dorothy Tanur (1958–2002), an urban planner and lawyer who cared deeply […]

When presenting a new method, talk about its failure modes.

A coauthor writes: I really like the paper [we are writing] as it is. My only criticism of it perhaps would be that we present this great new method and discuss all of its merits, but we do not really discuss when it fails / what its downsides are. Are there any cases where the […]

On the term “self-appointed” . . .

I was reflecting on what bugs me so much about people using the term “self-appointed” (for example, when disparaging “self-appointed data police” or “self-appointed chess historians“). The obvious question when someone talks about “self-appointed” whatever is, Who self-appointed you to decide who is illegitimately self-appointed? But my larger concern is with the idea that being […]

What’s the p-value good for: I answer some questions.

Martin King writes: For a couple of decades (from about 1988 to 2006) I was employed as a support statistician, and became very interested in the p-value issue; hence my interest in your contribution to this debate. (I am not familiar with the p-value ‘reconciliation’ literature, as published after about 2005.) I would hugely appreciate […]

Automation and judgment, from the rational animal to the irrational machine

Virgil Kurkjian writes: I was recently going through some of your recent blog posts and came across Using numbers to replace judgment. I recently wrote something about legible signaling which I think helps shed some light on exactly what causes the bureaucratization of science and maybe what we can do about it. In short I […]

Are statistical nitpickers (e.g., Kaiser Fung and me) getting the way of progress or even serving the forces of evil?

As Ira Glass says, today we have a theme and some variations on this theme. Statistical nitpickers: Do they cause more harm than good? I’d like to think we cause more good than harm, but today I want to consider the counter-argument, that, even when we are correct on the technical merits, we statisticians should […]

More on that 4/20 road rage researcher: Dude could be a little less amused, a little more willing to realize he could be on the wrong track with a lot of his research.

So, back on 4/20 we linked to the post by Sam Harper and Adam Palayew shooting down a silly article, published in JAMA and publicized around the world, that claimed excess road deaths on 4/20 (“cannabis day”). I googled the authors of that silly JAMA paper and found that one of them, Dr. Donald Redelmeier, […]

“Less Wow and More How in Social Psychology”

Fritz Strack sends along this article from 2012 which has an interesting perspective. Strack’s article begins: But, he continues, things changed in 2011 with the scandals of Diederik Stapel (a career built upon fake data), Daryl Bem (joke science getting published in a real journal), and a seemingly unending series of prominent studies that failed […]

“Troubling Trends in Machine Learning Scholarship”

Garuav Sood writes: You had expressed slight frustration with some ML/CS papers that read more like advertisements than anything else. The attached paper by Zachary Lipton and Jacob Steinhardt flags four reasonable concerns in modern ML papers: Recent progress in machine learning comes despite frequent departures from these ideals. In this paper, we focus on […]

Glenn Shafer tells us about the origins of “statistical significance”

Shafer writes: It turns out that Francis Edgeworth, who introduced “significant” in statistics, and Karl Pearson, who popularized it in statistics, used it differently than we do. For Edgeworth and Pearson, “being significant” meant “signifying”. An observed difference was significant if it signified a real difference, and you needed a very small p-value to be […]

Junk science and fake news: Similarities and differences

Jingyi Kenneth Tay writes: As I read your recent post, “How Sloppy Science Creates Worthless Cures, Crushes Hope, and Wastes Billions” . . . and still stays around even after it’s been retracted, I realized that there are many similarities between this and fake news: how it is much easier to put fake news out […]

Funny citation-year thing

So, I’m going through the final draft of Regression and Other Stories, adding index entries, cleaning up references, etc., and I noticed this: Yes, I cite myself a lot—sometimes people call it “self-citation” and act like it’s a bad thing—but I think it’s helpful to point people to my earlier writings on various topics. Anyway, […]

They misreport their experiments and don’t fess up when they’ve been caught.

Javier Benitez points us to this paper, “COMPare: Qualitative analysis of researchers’ responses to critical correspondence on a cohort of 58 misreported trials,” by Ben Goldacre, Henry Drysdale, Cicely Marston, Kamal Mahtani, Aaron Dale, Ioan Milosevic, Eirion Slade, Philip Hartley and Carl Heneghan, who write: Discrepancies between pre-specified and reported outcomes are an important and […]

The State of the Art

Jesse Singal writes: This was presented, in Jennifer Eberhardt’s book Biased, as evidence to support the idea that even positive portrayals of black characters could be spreading and exacerbating unconscious antiblack bias. I did not see evidence to support that idea. I replied: I don’t understand what you’re saying here. I clicked thru and the […]

“Suppose that you work in a restaurant…”

In relation to yesterday’s post on Monty Hall, Josh Miller sends along this paper coauthored with the ubiquitous Adam Sanjurjo, “A Bridge from Monty Hall to the Hot Hand: The Principle of Restricted Choice,” which begins: Suppose that you work in a restaurant where two regular customers, Ann and Bob, are equally likely to come […]

“Superior: The Return of Race Science,” by Angela Saini

“People so much wanted the story to be true . . . that they couldn’t look past it to more mundane explanations.” – Angela Saini, Superior. I happened to be reading this book around the same time as I attended the Metascience conference, which was motivated by the realization during the past decade or so […]

“Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science”

As promised, let’s continue yesterday’s discussion of Christopher Tong’s article, “Statistical Inference Enables Bad Science; Statistical Thinking Enables Good Science.” First, the title, which makes an excellent point. It can be valuable to think about measurement, comparison, and variation, even if commonly-used statistical methods can mislead. This reminds me of the idea in decision analysis […]