Skip to content
Archive of posts filed under the Miscellaneous Statistics category.


Leonid Schneider writes: I am cell biologist turned science journalist after 13 years in academia. Despite my many years experience as scientist, I shamefully admit to be largely incompetent in statistics. My request to you is as follows: A soon to be published psychology study set on to reproduce 100 randomly picked earlier studies and […]


Reflecting on the recent psychology replication study (see also here), journalist Megan McArdle writes an excellent column on why we fall for bogus research: The problem is not individual research papers, or even the field of psychology. It’s the way that academic culture filters papers, and the way that the larger society gets their results. […]

P-values and statistical practice

What is a p-value in practice? The p-value is a measure of discrepancy of the fit of a model or “null hypothesis” H to data y. In theory the p-value is a continuous measure of evidence, but in practice it is typically trichotomized approximately into strong evidence, weak evidence, and no evidence (these can also […]

To understand the replication crisis, imagine a world in which everything was published.

John Snow points me to this post by psychology researcher Lisa Feldman Barrett who reacted to the recent news on the non-replication of many psychology studies with a contrarian, upbeat take, entitled “Psychology Is Not in Crisis.” Here’s Barrett: An initiative called the Reproducibility Project at the University of Virginia recently reran 100 psychology experiments […]

Uri Simonsohn warns us not to be falsely reassured

I agree with Uri Simonsohn that you don’t learn much by looking at the distribution of all the p-values that have appeared in some literature. Uri explains: Most p-values reported in most papers are irrelevant for the strategic behavior of interest. Covariates, manipulation checks, main effects in studies testing interactions, etc. Including them we underestimate […]

My 2 classes this fall

Stat 6103, Bayesian Data Analysis Modern Bayesian methods offer an amazing toolbox for solving science and engineering problems. We will go through the book Bayesian Data Analysis and do applied statistical modeling using Stan, using R (or Python or Julia if you prefer) to preprocess the data and postprocess the analysis. We will also discuss […]

Neither time nor stomach

Mark Palko writes: Thought you might be interested in an EngageNY lesson plan for statistics. So far no (-2)x(-2) = -4 (based on a quick read), but still kind of weak. It bothers me that they keep talking about randomization but only for order of test; they assigned treatment A to the first ten of […]

Dan Kahan doesn’t trust the Turk

Dan Kahan writes: I [Kahan] think serious journals should adopt policies announcing that they won’t accept studies that use M Turk samples for types of studies they are not suited for. . . . Here is my proposal: Pending a journal’s adoption of a uniform policy on M Turk samples, the journal should should oblige […]

If you leave your datasets sitting out on the counter, they get moldy

I received the following in the email: I had a look at the dataset on speed dating you put online, and I found some big inconsistencies. Since a lot of people are using it, I hope this can help to fix them (or hopefully I did a mistake in interpreting the dataset). Here are the […]

“We can keep debating this after 11 years, but I’m sure we all have much more pressing things to do (grants? papers? family time? attacking 11-year-old papers by former classmates? guitar practice?)”

Someone pointed me to this discussion by Lior Pachter of a controversial claim in biology. The statistics The statistical content has to do with a biology paper by M. Kellis, B. W. Birren, and E.S. Lander from 2004 that contains the following passage: Strikingly, 95% of cases of accelerated evolution involve only one member of […]

Ira Glass asks. We answer.

The celebrated radio quiz show star says: There’s this study done by the Pew Research Center and Smithsonian Magazine . . . they called up one thousand and one Americans. I do not understand why it is a thousand and one rather than just a thousand. Maybe a thousand and one just seemed sexier or […]

Measurement is part of design

The other day, in the context of a discussion of an article from 1972, I remarked that the great statistician William Cochran, when writing on observational studies, wrote almost nothing about causality, nor did he mention selection or meta-analysis. It was interesting that these topics, which are central to any modern discussion of observational studies, […]

Survey weighting and regression modeling

Yphtach Lelkes points us to a recent article on survey weighting by three economists, Gary Solon, Steven Haider, and Jeffrey Wooldridge, who write: We start by distinguishing two purposes of estimation: to estimate population descriptive statistics and to estimate causal effects. In the former type of research, weighting is called for when it is needed […]

Don’t do the Wilcoxon

The Wilcoxon test is a nonparametric rank-based test for comparing two groups. It’s a cool idea because, if data are continuous and there is no possibility of a tie, the reference distribution depends only on the sample size. There are no nuisance parameters, and the distribution can be tabulated. From a Bayesian point of view, […]

Inauthentic leadership? Development and validation of methods-based criticism

Thomas Basbøll writes: I need some help with a critique of a paper that is part of the apparently growing retraction scandal in leadership studies. Here’s Retraction Watch. The paper I want to look at is here: “Authentic Leadership: Development and Validation of a Theory-Based Measure” By F. O. Walumbwa, B. J. Avolio, W. L. […]

Discreteland and Continuousland

Roy Mendelssohn points me to this paper by Jianqing Fan, Qi-Man Shao, and Wen-Xin Zhou, “Are Discoveries Spurious? Distributions of Maximum Spurious Correlations and Their Applications.” I never know what to think about these things because I don’t work in a discrete world in which there are zero effects (see our earlier discussion of the […]

“Menstrual Cycle Phase Does Not Predict Political Conservatism”

Someone pointed me to this article by Isabel Scott and Nicholas Pound: Recent authors have reported a relationship between women’s fertility status, as indexed by menstrual cycle phase, and conservatism in moral, social and political values. We conducted a survey to test for the existence of a relationship between menstrual cycle day and conservatism. 2213 […]

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. […]

What’s So Fun About Fake Data?

Our first Daily Beast column is here.

Our new column in the Daily Beast

Kaiser Fung and I have a new weekly column for the Daily Beast. After much deliberation, we gave it the title Statbusters (the runner-up choice was Dirty Data; my personal preference was Statboyz in the Hood, but, hey, who ever listens to me on anything?). The column will appear every Saturday, and Kaiser and I […]