Statistics has a pretty interesting stigma in science. <i>It's something you're not allowed to question.</i> Generally.<p>You can question if someone's models are right. You can question if their controls narrowed the experiment well enough. You can question if their interpretation makes any sense. What you can't question is if something like a t-test, LLS, or ANOVA is the best way to pull meaningful parameters out of the data. Just look at how much resistance Bayesian methods face in publication.<p>This is a fundamental friction that statistics has to overcome as long as its still called statistics. I think of ML as the parts of statistical research that escaped through the window opened by Shannon back when he invented information theory. It's a bird now, free to invent its words for the world and try crazy stuff that the religion of "Statistics" could never accept.<p>This isn't to say that Statistics isn't growing. The article itself does a good job pointing out just how similar recent Stat has been to ML. However, if you see a research paper in some of the more core, less data intensive sciences that dares to drop "SVM", "Ridge Regression", "Clustering", "Bayes", or god forbid "Machine Learning" itself you see scowls: isn't your data <i>normal enough</i>? Why do you need to do something fancy when I can work out the z-score of that result right here on my pocket calculator/slide rule.<p>(<i>Lets go ahead and concede that ML certainly has a lot of broken yet overhyped parts which helps form the nucleus of an argument not to infect scientific knowledge with some untested infrastructure. Growing pains.</i>)<p>It's a classic fight between tradition and innovation with all the usual arguments available, but what makes this different is that such a huge community of people who thrive off the image of really, <i>really</i> knowing things pretty much take the frequentist methodologies as an unimpeachable gold standard. Things can get dicey when you start to ask what the actual meaning of a p-value is, how we really know anything about "estimators", why people work so hard not to use computers. <i>It works! Stop asking questions.</i>