This post shamelessly plagiarizes liberally borrows ideas from a much longer, more detailed, and just generally better post by Cosma Shalizi. I’m not apologetic, since I’m a firm believer in the notion that good ideas should be repeated often and loudly. So I’m going to be often and loud here, though I’ll try to be … Continue reading what the general factor of intelligence is and isn’t, or why intuitive unitarianism is a lousy guide to the neurobiology of higher cognitive ability
Craig Bennett and Mike Miller have a new paper on the reliability of fMRI. It’s a nice review that I think most people who work with fMRI will want to read. Bennett and Miller discuss a number of issues related to reliability, including why we should care about the reliability of fMRI, what factors influence … Continue reading functional MRI and the many varieties of reliability
Continuing along on their guided tour of Data I Wish I Had Access To, the OKCupid folks have posted another set of interesting figures on their blog. This time, they make the case for dating older women, suggesting that men might get more bang for their buck (in a literal sense, I suppose) by trying … Continue reading the OKCupid guide to dating older women
What follows is a fictional piece about sheep and statistics. I wrote it about two years ago, intending it to serve as a preface to an article on the dangers of inadvertent data fudging. But then I decided that no journal editor in his or her right mind would accept an article that started out … Continue reading the parable of zoltan and his twelve sheep, or why a little skepticism goes a long way
Drew Conway has a great list of 10 must-have R packages for social scientists. If you’re a social scientist (or really, any kind of scientist) who doesn’t use R, now is a great time to dive in and learn; there are tons of tutorials and guides out there (my favorite is Quick-R, which is incredibly … Continue reading got R? get social science for R!
The brain is a big place. In the context of fMRI analysis, what that bigness means is that a typical 3D image of the brain might contain anywhere from 50,000 – 200,000 distinct voxels (3D pixels). Any of those voxels could theoretically show meaningful activation in relation to some contrast of interest, so the only … Continue reading specificity statistics for ROI analyses: a simple proposal
Andrew Gelman posted a link on his blog today to a paper by John Ioannidis I hadn’t seen before. In many respects, it’s basically the same paper I wrote earlier this year as a commentary on the Vul et al “voodoo correlations” paper (the commentary was itself based largely on an earlier chapter I wrote … Continue reading Ioannidis on effect size inflation, with guest appearance by Bozo the Clown