Yeah, I find it kind of funny when people compare a general purpose programming language with a statistical software. In R you have libraries for things like Apprximate Bayesian Computation, parametric and non-parametric statistics, and even neural networks.
Sure, you could achieve the same with a general purpose PL, but you would have to implement everything from scratch.
JS does have a few (like jStat) but they're fairly young. Still, I don't think the article was suggesting that everybody should drop everything and jump on JS for statistics work. But it does raise the question of whether more focus should be put into the development of statistical libraries for JS.
Sure, you could achieve the same with a general purpose PL, but you would have to implement everything from scratch.