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 […]

**Statistical graphics**category.

## 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, […]

## Some ideas on using virtual reality for data visualization: I don’t really agree with the details here but it’s all worth discussing

Evan Warfel writes: Misleading graphs are one thing you consistently write about, and it seems to me that Virtual Reality has the potential to solve part of this problem — there is no point in sharing a “static” VR experience; instead, by allowing users to change the axes and interact with the data, they have […]

## Call for papers: Probabilistic Programming Languages, Semantics, and Systems (PPS 2018)

I’m on the program committee and they say they’re looking to broaden their horizons this year to include systems like Stan. The workshop is part of POPL, the big programming language theory conference. Here’s the official link PPS 2018 home page Call for extended abstracts (2 pages) The submissions are two-page extended abstracts and the […]

## Touch me, I want to feel your data.

(This is not a paper we wrote by mistake.) (This is also not Andrew) (This is also really a blog about an aspect of the paper, which mostly focusses on issues around visualisation and how visualisation can improve workflow. So you should read it.) Recently Australians have been living through a predictably ugly debate around […]

## Stan Weekly Roundup, 25 August 2017

This week, the entire Columbia portion of the Stan team is out of the office and we didn’t have an in-person/online meeting this Thursday. Mitzi and I are on vacation, and everyone else is either teaching, TA-ing, or attending the Stan course. Luckily for this report, there’s been some great activity out of the meeting […]

## Cumulative residual plots seem like they could be useful

Peter Vanney, a statistician at Texas Highway Patrol, writes: I’m wondering if you could comment on CURE (CUmulative REsidual) plots that I’m seeing quite a bit in vehicle crash modeling. Ezra Hauer and Joseph Bamfo champion them as a way to determine model fit for their hierarchical Bayesian generalized linear mixed models. I had not […]

## It is somewhat paradoxical that good stories tend to be anomalous, given that when it comes to statistical data, we generally want what is typical, not what is surprising. Our resolution of this paradox is . . .

From a blog comment a few years ago regarding an article by Robert Kosara: As Thomas and I discuss in our paper [When Do Stories Work? Evidence and Illustration in the Social Sciences], it is somewhat paradoxical that good stories tend to be anomalous, given that when it comes to statistical data, we generally want […]

## Applying human factors research to statistical graphics

John Rauser writes: I’ve been a reader of yours (books, papers and the blog) for a long time, and it occurred to me today that I might be able to give something back to you. I recently wrote a talk (https://www.youtube.com/watch?v=fSgEeI2Xpdc) about human factors research applied to making statistical graphics. I mainly cover material from […]

## Graphs as comparisons: A case study

Above is a pair of graphs from a 2015 paper by Alison Gopnik, Thomas Griffiths, and Christopher Lucas. It takes up half a page in the journal, Current Directions in Psychological Science. I think we can do better. First, what’s wrong with the above graphs? We could start with the details: As a reader, I […]

## Question about the secret weapon

Micah Wright writes: I first encountered your explanation of secret weapon plots while I was browsing your blog in grad school, and later in your 2007 book with Jennifer Hill. I found them immediately compelling and intuitive, but I have been met with a lot of confusion and some skepticism when I’ve tried to use […]

## After Peptidegate, a proposed new slogan for PPNAS. And, as a bonus, a fun little graphics project.

Someone pointed me to this post by “Neuroskeptic”: A new paper in the prestigious journal PNAS contains a rather glaring blooper. . . . right there in the abstract, which states that “three neuropeptides (β-endorphin, oxytocin, and dopamine) play particularly important roles” in human sociality. But dopamine is not a neuropeptide. Neither are serotonin or […]

## Hey—here are some tips on communicating data and statistics!

This fall I’ll be again teaching the course, Communicating Data and Statistics. Here’s the rough course plan. I’ll tinker with it between now and September but this is the basic idea. (The course listing is here, but that online description is out of date; the course plan linked above is more accurate.) Here are the […]