Quick public service announcement for my fellow R nerds: R has two commonly-used random-Normal generators: rnorm and MASS::mvrnorm. I was foolish and assumed that their parameterizations were equivalent when you’re generating univariate data. But nope: Base R can generate univariate … Continue reading → [Read more...]

I just heard about Data Proofer (h/t Nathan Yau), a test suite of sanity-checks for your CSV dataset. It checks a few basic things you’d really want to know but might forget to check yourself, like whether any rows are … Continue reading → [Read more...]

I’ve seen R users swooning over the magrittr package for a while now, but I couldn’t make heads or tails of all these scary %__% symbols. Finally I had time for a closer look, and it seems potentially handy indeed. … Continue reading → [Read more...]

I’ve just finished teaching the Fall 2015 session of 36-721, Statistical Graphics and Visualization. Again, it is a half-semester course designed primarily for students in the MSP program (Masters of Statistical Practice) in the CMU statistics department. I’m pleased that … Continue reading → [Read more...]

I’m pretty excited for tomorrow: I’ll begin teaching the Fall 2015 offering of 36-721, Statistical Graphics and Visualization. This is a half-semester course designed primarily for students in our MSP program (Masters in Statistical Practice). A large part of the … Continue reading → [Read more...]

The first time I read John Cook’s advice “Don’t invert that matrix,” I wasn’t sure how to follow it. I was familiar with manipulating matrices analytically (with pencil and paper) for statistical derivations, but not with implementation details in software. … Continue reading → [Read more...]

Yesterday I spoke at Stat Bytes, our student-run statistical computing seminar. My goal was to introduce two principled frameworks for thinking about data visualization: human visual perception and the Grammar of Graphics. (We also covered some relevant R packages: RColorBrewer, … Continue reading → [Read more...]

A while back I recommended Nathan Uyttendaele’s beginner’s guide to speeding up R code. I’ve just heard about Nathan’s computer game project, DotCity. It sounds like a statistician’s minimalist take on SimCity, with a special focus on demographic shifts in … Continue reading → [Read more...]

TL;DR: Memento mori. After reading too much Seneca, I’m meditating on death like a statistician, by counting how many of GRRM’s readers did not even survive to see the HBO show (much less the end of the book series). Rough … Continue reading → [Read more...]

I never got around to polishing my Small Area Estimation (SAE) “101” tutorial materials that I promised a while ago. So here they are, though still unedited and not as clean / self-explanatory as I’d like. The slides introduce a … Continue reading → [Read more...]

Nathan Uyttendaele has written a great beginner’s guide to speeding up your R code. Abstract: Most calculations performed by the average R user are unremarkable in the sense that nowadays, any computer can crush the related code in a matter … Continue reading → [Read more...]

Last week I gave a short talk at CMU’s statistical computing seminar, Stat Bytes. I summarized why reproducible research (RR) and literate programming are worthwhile, not just for serious research but also for homework reports or statistical blog posts. I … Continue reading → [Read more...]

Have you ever wondered whether the first semester of a PhD is really all that busy? My complete lack of posts last fall should prove it Some thoughts on the Fall term, now that Spring is well under way: The … Continue reading → [Read more...]

In his talk “Give Your Data A Listen” at last summer’s useR! 2012 conference, Eric Stone presented joint work with Jesse Garrison on audiolyzR, an R package for “data sonification.” I thought this was a nifty and well-executed idea. Since I haven’t seen … Continue reading → [Read more...]

I really enjoyed tonight’s DC R Meetup, presented by the prolific Anthony Damico. [Edit: adding link to the full video of Anthony's talk; review is below.] I’ve met Anthony before to discuss whether the Census Bureau could either… publish R-readable … Continue reading → [Read more...]

(Video link here, in case the embedded player doesn’t work for you.) Idea: see if I can mimic the idea behind Ben Schmidt’s lovely video of ocean shipping routes, and apply it to another dataset. But which? “Hmm… what’s another … Continue reading → [Read more...]

Thank you all for the positive responses to Basics of JavaScript and D3 for R Users! Quick update: last time we had to dabble in a tiny bit of Python to start a local server, in order to actually run JavaScript … Continue reading → [Read more...]

Hadley Wickham, creator of the ggplot2 R package, has been learning JavaScript and its D3 library for the next iteration of ggplot2 (tentatively titled r2d3?)… so I suspect it’s only a matter of time before he pulls the rest of the … Continue reading → [Read more...]

Continuing the summary of last week’s symposium on statistics and data visualization (see part 1 and part 3)… Here I describe Dianne Cook’s discussion of visual inference, and Rob Kass’ talk on statistics in cognitive neuroscience. [Edit: I've added a few … Continue reading → [Read more...]

I love Nathan Yau’s tutorial on making choropleths from a SVG file. However, if you don’t have a SVG handy already and instead you want to repurpose a map from another vector format such as PDF or EPS, there are … Continue reading → [Read more...]