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, […]

**Statistical graphics**category.

## 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 […]

## You’ll never guess this one quick trick to diagnose problems with your graphs and then make improvements

The trick is to consider graphs as comparisons. Here’s the story. This post from several years ago shows a confusing and misleading pair of pie charts from a Kenyan election: The quick reaction would be to say, ha ha, pie charts. But that’s not my point here. Sure, pie charts have problems and I think […]

## More graphs of mortality trends

Corinne Riddell writes: In late March you released a series of plots visualizing mortality rates over time by race and gender. For almost a year now, we’ve been working on a similar project and have compiled all of our findings into an R shiny web app here, with a preprint of our first manuscript here. […]

## Click-through graphics: A demonstration visualization project for someone

Hey, read this post. We discuss a shiny information visualization and propose “the click-through solution”: Start with a visually grabby graphic like the one on the linked page, something that takes advantage of some mystery to suck the viewer in. Then click and get a suite of statistical graphs that allow more direct visual comparisons […]

## Mike Bostock graphs federal income tax brackets and tax rates, and I connect to some general principles of statistical graphics

Mike “d3” Bostock writes: Regarding the Vox graph on federal tax brackets, here is a quick-and-dirty visualization of effective tax rates for a given taxable income and year. However, there is a big caveat: estimating the effective tax rate based on actual income is much harder since it depends on the claimed deductions. This could […]

## Taxes and data visualization

Nadia Hassan writes: Vox has a graph of tax rates over time. Their visualizations do convey that tax rates for high earners have declined over time and tax brackets are fewer now, but it seems like there are more appealing and intuitive ways to display that. I agree. This visualization reminds me a lot of […]

## Visualizing your fitted Stan model using ShinyStan without interfering with your Rstudio session

ShinyStan is great, but I don’t always use it because when you call it from R, it freezes up your R session until you close the ShinyStan window. But it turns out that it doesn’t have to be that way. Imad explains: You can open up a new session via the RStudio menu bar (Session […]

## Blue Cross Blue Shield Health Index

Chris Famighetti points us to this page which links to an interactive visualization. There are some problems with the mapping software—when I clicked through, it showed a little map of the western part of the U.S., accompanied by huge swathes of Canada and the Pacific Ocean—and I haven’t taken a look at the methodology. But […]

## 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 […]