[Edit, Sept. 25, 2016: In retrospect, this is a confusing post. The overall point is fine, but my contrived illustration is not a good one.] At an otherwise excellent talk some time ago, the speaker put up a graph like this (look below — not the cheetah)… …and said that the two sets of data points, … Continue reading You may not be interested in noise, but noise is interested in you
Synopsis: (1) We’re posting preprints, for the reasons that you’re probably already familiar with. (2) I can entertain myself by making graphs and models, this time about article metrics. Preprints A few months ago we posted our first, and a few weeks ago our second, papers on bioRxiv, the fairly new preprint server for life … Continue reading We’re Hip, We’re Trendy, We’re Pre-printers
[Note: a long post of interest only to people who care about data analysis and bad statistics, and maybe about the distant stars influencing your life.] By now, we should all be able to list the many reasons that p-values (or null-hypothesis-significance-testing, NHST) are awful: that “statistical significance” has nothing to do with effect size … Continue reading How do I hate p-values? Let me count the ways…
In Part I, I wrote about how I started exploring the topic of machine learning, and we looked briefly described one of its main aims: automating the task of classifying objects based on their properties. Here, I’ll give an example of this in action, and also describe some general lessons I’ve drawn from this experience. … Continue reading Learning about (machine) learning — part II
Machine learning is everywhere these days, as we train computers to drive cars, play video games, and fold laundry. This intersects my lab’s research as well, which involves lots of computational image analysis (e.g.). Nearly everything my students and I write involves writing or applying particular algorithms to extract information from data. In the past … Continue reading Learning about (machine) learning — Part I
A long post, in which you’ll have to slog or scroll through several paragraphs to get to the real question: can we navigate using fallen sticks? These days we seem to be inundated with deeply flawed scientific papers, often featuring shaky conclusions boldly drawn from noisy data, results that can’t be replicated, or both. I … Continue reading On the replication crisis in science and the twigs in my backyard
As of yesterday, the graduate student union here at the University of Oregon is on strike*. (I walked past three separate picket lines on my way to get coffee.) I don’t have anything profound to write about labor issues, but I thought I should post something that’s graduate-student-related! Quite often, the topic of “time to … Continue reading Universality, Scaling, and Time-to-Ph.D.