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Archive of posts filed under the Statistical graphics category.

Aggregate age-adjusted trends in death rates for non-Hispanic whites and minorities in the U.S.

Following up on our recent Slate article, Jonathan Auerbach made some graphs of mortality rate trends by sex, ethnicity, and age group, aggregating over the entire country. Earlier we’d graphed the trends within each state but there was so much going on there, it was hard to see the big picture. All our graphs are […]

Easier-to-download graphs of age-adjusted mortality trends by sex, ethnicity, and age group

Jonathan Auerbach and I recently created graphs of smoothed age-adjusted mortality trends from 1999-2014 for: – 50 states – men and women – non-hispanic whites, blacks, and hispanics – age categories 0-1, 1-4, 5-14, 15-24, 25-34, 35-44, 45-54, 55-64, 65-74, 75-84. We posted about this on the blog and also wrote an article for Slate […]

Crack Shot

Raghu Parthasarathy writes: You might find this interesting, an article (and related essay) on the steadily declining percentage of NIH awards going to mid-career scientists and the steadily increasing percentage going to older researchers. The key figure is below. The part that may be of particular interest to you, since you’ve written about age-adjustment in demographic work: does […]

Some U.S. demographic data at zipcode level conveniently in R

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 […]

An exciting new entry in the “clueless graphs from clueless rich guys” competition

Jeff Lax points to this post from Matt Novak linking to a post by Matt Taibbi that shares the above graph from newspaper columnist / rich guy Thomas Friedman. I’m not one to spend precious blog space mocking bad graphs, so I’ll refer you to Novak and Taibbi for the details. One thing I do […]

“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: 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 […]

Gray graphs look pretty

Swupnil made this graph for a research meeting we had today: It looks so cool. I think it’s the gray colors. So here’s my advice to you: If you want to make your graphs look cool, use lots of gray.

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 […]

Graph too clever by half

Mike Carniello writes: I wondered what you make of this. I pay for the NYT online and tablet – but not paper, so I don’t know how they’re representing this content in two dimensions. I’ve paged through the thing a couple of times, not sure how useful it is – it seems like a series […]


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 […]