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Archive of posts filed under the Statistical graphics category.

I actually think this infographic is ok

Under the heading, “bad charts,” Mark Duckenfield links to this display by Quoctrung Bui and writes: So much to go with here, but I [Duckenfield] would just highlight the bars as the most egregious problem as it is implied that the same number of people are in each category. Obviously that is not the case […]

In criticism of criticism of criticism

I do a lot of criticism. I’m sure you can think of lots of things that I like to criticize, but to keep things simple, let’s focus on graphics criticism, for example this post where I criticized a graph for false parallelism. At this point some people would say that graphics criticism is mean, and […]

Forget about pdf: this looks much better, it makes all my own papers look like kids’ crayon drawings by comparison.

Mark Palko points me to this webpage which presents a recent research paper by Joanna Shepherd and Michael Kang. I have no comment on the research—I haven’t had a chance to read the paper—but I wanted to express how impressed I was about the presentation. It starts with a dedicated url just for this paper […]

Go to PredictWise for forecast probabilities of events in the news

I like it. Clear, transparent, no mumbo jumbo about their secret sauce. But . . . what’s with the hyper-precision: C’mon. “27.4%”? Who are you kidding?? (See here for explication of this point.)

“For better or for worse, academics are fascinated by academic rankings . . .”

I was asked to comment on a forthcoming article, “Statistical Modeling of Citation Exchange Among Statistics Journals,” by Christiano Varin, Manuela Cattelan and David Firth. Here’s what I wrote: For better or for worse, academics are fascinated by academic rankings, perhaps because most of us reached our present positions through a series of tournaments, starting […]

“Another bad chart for you to criticize”

Perhaps in response to my lament, “People used to send me ugly graphs, now I get these things,” Stuart Buck sends me an email with the above comment and a link to this “Graphic of the day” produced by some uncredited designer at Thomson Reuters: From a statistical perspective, this graph is a disaster in […]

The publication of one of my pet ideas: Simulation-efficient shortest probability intervals

In a paper to appear in Statistics and Computing, Ying Liu, Tian Zheng, and I write: Bayesian highest posterior density (HPD) intervals can be estimated directly from simulations via empirical shortest intervals. Unfortunately, these can be noisy (that is, have a high Monte Carlo error). We derive an optimal weighting strategy using bootstrap and quadratic […]

Interactive demonstrations for linear and Gaussian process regressions

Here’s a cool interactive demo of linear regression where you can grab the data points, move them around, and see the fitted regression line changing. There are various such apps around, but this one is particularly clean: (I’d like to credit the creator but I can’t find any attribution at the link, except that it’s […]

Defaults, once set, are hard to change.

So. Farewell then Rainbow color scheme. You reigned in Matlab Far too long. But now that You are no longer The default, Will we miss you? We can only Visualize. E. T. Thribb (17 1/2) Here’s the background.  Brad Stiritz writes: I know you’re a creator and big proponent of open-source tools. Given your strong interest […]

Introducing shinyStan

As a project for Andrew’s Statistical Communication and Graphics graduate course at Columbia, a few of us (Michael Andreae, Yuanjun Gao, Dongying Song, and I) had the goal of giving RStan’s print and plot functions a makeover. We ended up getting a bit carried away and instead we designed a graphical user interface for interactively exploring virtually […]