Like many mathematical topics, statistics can be persistently abstract and unintuitive. From dividing by n-1 instead of n, to proving results in infinite dimensional Hilbert spaces, statistics rarely goes down smooth on the first try. Most of the best statisticians take this challenge head on. They can quickly distill the Read More
At some point or another, many of us have heard the quote popularized by Mark Twain, that “there are three kinds of lies: lies, damned lies, and statistics.” For a long time, my response was to snarkily question Twain’s statistical training — I would say that he was writing Read More
Statisticians and computer scientists often use the term “gold standard” for the best possible benchmark you could have when trying to estimate something. For example, Elizabeth Sweeney has worked on algorithms for tagging brain lesions in MRIs, and compares the results against a gold standard of human neurologists attempting Read More
Check out this lovely brain image figure! I wrote an R package called ggBrain that lets you generate figures like these with just a couple lines of code!
This figure is from my recent paper on fast, exact methods for bootstrapping high dimensional data (>1 million measurements per subject). When Read More
I sometimes hear people say that they wish they could’ve gone to Hogwarts School of Witchcraft and Wizardry (HSWW), but there’s a drawback of HSWW that’s often overlooked. You can do a lot with a degree from HSWW, but the one thing that’s hard to do is to become a Read More
In this blog, I’ll talk about issues in statistics from a graduate student’s perspective. Some specific topics include: surviving a PhD, enjoying a PhD, designing intuitive graphics, and dealing with high dimensional data. There will also be musings from time to time about food/cooking (i.e. JHSPH Biostat Chili Cookoff Read More