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Archive of posts filed under the Statistical graphics category.

What’s gonna happen in the 2018 midterm elections?

Following up on yesterday’s post on party balancing, here’s a new article from Joe Bafumi, Bob Erikson, and Chris Wlezien giving their predictions for November: We forecast party control of the US House of Representatives after the 2018 midterm election. First, we model the expected national vote relying on available generic Congressional polls and the […]

Awesome MCMC animation site by Chi Feng! On Github!

Sean Talts and Bob Carpenter pointed us to this awesome MCMC animation site by Chi Feng. For instance, here’s NUTS on a banana-shaped density. This is indeed super-cool, and maybe there’s a way to connect these with Stan/ShinyStan/Bayesplot so as to automatically make movies of Stan model fits. This would be great, both to help […]

Should the points in this scatterplot be binned?

Someone writes: Care to comment on this paper‘s Figure 4? I found it a bit misleading to do scatter plots after averaging over multiple individuals. Most scatter plots could be “improved” this way to make things look much cleaner than they are. People are already advertising the paper using this figure. The article, Genetic analysis […]

Opportunity for Comment!

(This is Dan) Last September, Jonah, Aki, Michael, Andrew and I wrote a paper on the role of visualization in the Bayesian workflow.  This paper is going to be published as a discussion paper in the Journal of the Royal Statistical Society Series A and the associated read paper meeting (where we present the paper and […]

“Choose the data visualization that best serves your audience.”

Tian Zheng prepared the above slide which very clearly displays an important point about statistical communication. The maps are squished to be too narrow, and the scatterplot has too many numbers on the axes (better to have income in thousands and percentages in tens), also given the numbers it seems that the data must be […]

Awesome data visualization tool for brain research

When I was visiting the University of Washington the other day, Ariel Rokem showed me this cool data visualization and exploration tool produced by Jason Yeatman, Adam Richie-Halford, Josh Smith, and himself. The above image gives a sense of the dashboard but the real thing is much more impressive because it’s interactive. You can rotate […]

The current state of the Stan ecosystem in R

(This post is by Jonah) Last week I posted here about the release of version 2.0.0 of the loo R package, but there have been a few other recent releases and updates worth mentioning. At the end of the post I also include some general thoughts on R package development with Stan and the growing number of […]

Taking perspective on perspective taking

Gabor Simonovits writes: I thought you might be interested in this paper with Gabor Kezdi of U Michigan and Peter Kardos of Bloomfield College, about an online intervention reducing anti-Roma prejudice and far-right voting in Hungary through a role-playing game. The paper is similar to some existing social psychology studies on perspective taking but we […]

“The problem of infra-marginality in outcome tests for discrimination”

Camelia Simoiu, Sam Corbett-Davies, and Sharad Goel write: Outcome tests are a popular method for detecting bias in lending, hiring, and policing decisions. These tests operate by comparing the success rate of decisions across groups. For example, if loans made to minority applicants are observed to be repaid more often than loans made to whites, […]

Wanna know what happened in 2016? We got a ton of graphs for you.

The paper’s called Voting patterns in 2016: Exploration using multilevel regression and poststratification (MRP) on pre-election polls, it’s by Rob Trangucci, Imad Ali, Doug Rivers, and myself, and here’s the abstract: We analyzed 2012 and 2016 YouGov pre-election polls in order to understand how different population groups voted in the 2012 and 2016 elections. We […]

Here’s the title of my talk at the New York R conference, 20 Apr 2018:

The intersection of Graphics and Bayes, a slice of the Venn diagram that’s a lot more crowded than you might realize And here are some relevant papers: [2003] A Bayesian formulation of exploratory data analysis and goodness-of-fit testing. {\em International Statistical Review} {\bf 71}, 369–382. (Andrew Gelman) [2004] Exploratory data analysis for complex models (with […]

Hey—here’s the title of my talk for this year’s New York R conference

Toward a Fuller Integration of Graphics in Statistical Analysis The talk will be 20 Apr 2018 at 1:25pm. And here are some things to read ahead of time, if you’re interested: [2003] A Bayesian formulation of exploratory data analysis and goodness-of-fit testing. {\em International Statistical Review} {\bf 71}, 369–382. [2004] Exploratory data analysis for complex […]

Interactive visualizations of sampling and GP regression

You really don’t want to miss Chi Feng‘s absolutely wonderful interactive demos. (1) Markov chain Monte Carlo sampling I believe this is exactly what Andrew was asking for a few Stan meetings ago: Chi Feng’s Interactive MCMC Sampling Visualizer This tool lets you explore a range of sampling algorithms including random-walk Metropolis, Hamiltonian Monte Carlo, […]

How to improve this visualization of voting in the U.S. Congress?

Richie Lionell points us to this interactive visualization of votes of U.S. Senators. It’s attractive. My big problem is that nothing is conveyed by the positions of the points along the circles. Thus, that cute image of the points moving around is a bit misleading. Maybe someone has a suggestion of how to do this […]

“Dear Professor Gelman, I thought you would be interested in these awful graphs I found in the paper today.”

Mike Sances writes: I thought you would be interested in these awful graphs I found in the paper today. Sample attached [see above], but the article is full of them. My reply: This is indeed horrible in so many ways. I hope nobody was looking at that graph on their phone while driving! At the […]

Graphics software is not a tool that makes your graphs for you. Graphics software is a tool that allows you to make your graphs.

I had an email exchange with someone the other day. He had a paper with some graphs that I found hard to read, and he replied by telling me about the software he used to make the graphs. It was fine software, but the graphs were, nonetheless, unreadable. Which made me realize that people are […]

Tips when conveying your research to policymakers and the news media

Following up on a conversation regarding publicizing scientific research, Jim Savage wrote: Here’s a report that we produced a few years ago on prioritising potential policy levers to address the structural budget deficit in Australia. In the report we hid all the statistical analysis, aiming at an audience that would feel comfortable reading a broadsheet […]

Contour as a verb

Our love is like the border between Greece and Albania – The Mountain Goats (In which I am uncharacteristically brief) Andrew’s answer to recent post reminded me of one of my favourite questions: how do you visualise uncertainty in spatial maps.  An interesting subspecies of this question relates to exactly how you can plot a contour […]

An alternative to the superplot

Kevin Brown writes: I came across the lexicon link to your ‘super plots’ posting today. In it, you plot the association between individual income (X) and republican voting (Y) for 3 states: one assumed to be poor, one middle income, and one wealthy. An alternative way of plotting this, what I call a ‘herd effects […]

Workshop on Interpretable Machine Learning

Andrew Gordon Wilson sends along this conference announcement: NIPS 2017 Symposium Interpretable Machine Learning Long Beach, California, USA December 7, 2017 Call for Papers: We invite researchers to submit their recent work on interpretable machine learning from a wide range of approaches, including (1) methods that are designed to be more interpretable from the start, […]