Ari Lamstein writes: I chuckled when I read your recent “R Sucks” post. Some of the comments were a bit … heated … so I thought to send you an email instead. I agree with your point that some of the datasets in R are not particularly relevant. The way that I’ve addressed that is […]

**Statistical graphics**category.

## “Another terrible plot”

Till Hoffman sent me an email with the above subject line and the following content: These plots from the Daily Mail in the UK probably belong in your hall of fame of terrible visualisations: http://www.dailymail.co.uk/news/article-3655775/The-polls-finally-open-Britain-s-historic-Referendum-vote-latest-polls-Remain-camp-lead-six-points-weather-swing-Brexit.html I was gonna click on this, but then I thought . . . the Daily Mail? Even I have limits […]

## No evidence shark attacks swing elections

Anthony Fowler and Andy Hall write: We reassess Achen and Bartels’ (2002, 2016) prominent claim that shark attacks influence presidential elections, and we find that the evidence is, at best, inconclusive. First, we assemble data on every fatal shark attack in U.S. history and county-level returns from every presidential election between 1872 and 2012, and […]

## Stan users group hits 2000 registrations

Of course, there are bound to be duplicate emails, dead emails, and people who picked up Stan, joined the list, and never came back. But still, that’s a lot of people who’ve expressed interest! It’s been an amazing ride that’s only going to get better as we learn more and continue to improve Stan’s speed […]

## Garrison Keillor would be spinning etc.

Under the subject line, “Misleading Graphs of the Week,” Bill Jefferys sends along this: I agreed with Bill’s colleague Helen Read who wondered why should the 90th percentile be some magic number? Just change it to 85% or 95% or whatever and all the graphs will look different. Also kinda horrible that they’re presenting percentages […]

## DrawMyData

Robert Grant writes: This web page is something I constructed recently. You might find it useful for making artificial datasets that demonstrate a particular point for students. At any rate, if you have any feedback on it I’d be interested to hear it. I’ve tried to keep it as simple as possible but in due […]

## All maps of parameter estimates remain misleading

Roland Rau writes: After many years of applying frequentist statistical methods in mortality research, I just began to learn about the application of Bayesian methods in demography. Since I also wanted to change a part of my research focus on spatial models, I discovered your 1999 paper with Phil Price, All maps of parameter estimates […]

## Euro 2016 update

Big news out of Europe, everyone’s talking about soccer. Leo Egidi updated his model and now has predictions for the Round of 16: Here’s Leo’s report, and here’s his zipfile with data and Stan code. The report contains some ugly histograms showing the predictive distributions of goals to be scored in each game. The R […]

## The NYT inadvertently demonstrates how not to make a graph

Andrew Hacker writes: I have the class prepare a report on how many households in the United States have telephones, land and cell. After studying census data, they focus on two: Connecticut and Arkansas, with respective ownerships of 98.9 percent and 94.6 percent. They are told they have to choose one of the following charts […]

## “Smaller Share of Women Ages 65 and Older Are Living Alone,” before and after age adjusment

After noticing this from a recent Pew Research report: Ben Hanowell wrote: This made me [Hanowell] think of your critique of Case and Deaton’s finding about non-Hispanic mortality. I wonder how much these results are driven by the fact that the population of adults aged 65 and older has gotten older with increasing lifespans, etc […]

## A Primer on Bayesian Multilevel Modeling using PyStan

Chris Fonnesbeck contributed our first PyStan case study (I wrote the abstract), in the form of a very nice Jupyter notebook. Daniel Lee and I had the pleasure of seeing him present it live as part of a course we were doing at Vanderbilt last week. A Primer on Bayesian Multilevel Modeling using PyStan This […]

## Who marries whom?

Elizabeth Heyman points us to this display by Adam Pearce and Dorothy Gambrell who write, “We scanned data from the U.S. Census Bureau’s 2014 American Community Survey—which covers 3.5 million households—to find out how people are pairing up.” They continue: For any selected occupation, the chart highlights the five most common occupation/relationship matchups. (For example, […]

## Ramanujan notes

A new movie on Ramanujan is coming out; mathematician Peter Woit gives it a very positive review, while film critic Anthony Lane is not so impressed. Both these reactions make sense, I guess (or so I say without having actually seen the movie myself). I’ll take this as an occasion to plug my article on […]

## All that really important statistics stuff that isn’t in the statistics textbooks

Kaiser writes: More on that work on age adjustment. I keep asking myself where is it in the Stats curriculum do we teach students this stuff? A class session focused on that analysis teaches students so much more about statistical thinking than anything we have in the textbooks. I’m not sure. This sort of analysis […]

## Birthday analysis—Friday the 13th update, and some model checking

Carl Bialik and Andrew Flowers at fivethirtyeight.com (Nate Silver’s site) ran a story following up on our birthdays example—that time series decomposition of births by day, which is on the cover of the third edition of Bayesian Data Analysis using data from 1968-1988, and which then Aki redid using a new dataset from 2000-2014. Friday […]

## Beautiful Graphs for Baseball Strike-Count Performance

This post is by Bob. I have no idea what Andrew will make of these graphs; I’ve been hoping to gather enough comments from him to code up a ggplot theme. Shravan, you can move along, there’s nothing here but baseball. Jim Albert created some great graphs for strike-count performance in a series of two […]

## Integrating graphs into your workflow

Discussion of statistical graphics typically focuses on individual graphs (for example here). But the real gain in your research comes from integrating graphs into your workflow. You want to be able to make the graphs you want, when you want them. At the same time, the graph have to be good enough that you can […]