(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs.)
Phillip Middleton writes in with two questions:
(1) Is html markdown or some other formatting script usable in comments? If so, what are the tags I may use?
(2) What are your views on the role of statistics in the evolution of the various folds of convergent science? For example, upon us there is this rather nebulously defined thing called data science which roughly equates to an amalgam of comp sci and stats. I tend to interpret it as somewhat computational stats, somewhat AI – or maybe it’s just an evolution of data mining, I don’t know yet.
The comp sci camp is marketing their brand in this area quite well. But is it me or is the statistical community perhaps taking a bit of a back seat? This feels more like a bit of competition than an invitation to converge ideas (so where does computational and graphical stats sit, then?). I had a brief conversation with Prof. Joe Blitzstein about this some time ago, and he expressed a number of concerns as well.
There are those that believe statisticians as a collective group have become less important in the work to translate data into meaning/knowledge than this unicorn (for now) ‘data scientist’. I believe part of the reason is that this new discipline has quite a bit of historical public ‘glitter’ and a few other shiny objects embedded (the term ‘big data’ for one, and a larger paycheck for another – quite the economically driven discipline), though it hasn’t in my opinion been fully defined. So what do you believe will become of it? Is it fad’ish or the storming/norming stage of a particular convergence between comp sci and stats? Or more?
I don’t see much official discussion by either groups like the ASA or any of the data science group/society outcroppings. What do you make of this? As much as I see the need for convergence in bayesian and frequentist philosophies in statistics, I see the need for convergence between the statistical and comp sci camps to solve problems which each alone may not necessarily be good at. Is that even a reasonable expectation?
Physics has been doing this quite rapidly in recent yrs. (convergence with medicine, biology, finance, economics, etc), and it has integrated fairly seamlessly I believe. I could be making the wrong comparison here, but it would seem to me statistics converges with, well….everything, and in no small way. Yet it seems to me there are forces ‘placing’ statistics as a whole into somewhat of a basement, or at least at the cusp of an identity crisis.
My reply:
(1) You can use html in comments. I’m not sure which are allowed and which aren’t, but, as I tell everyone, if your comment gets caught in the spam filter, just drop me an email. It happens.
(2) As I’ve written before (see also here), I think statistics (and machine learning, which I take to be equivalent to statistical inference but done by different people) is the least important part of data science. But I do think statistics has a lot to contribute, in design of data collection, model building, inference, and a general approach to making assumptions and evaluating their implications. Beyond this, I don’t really know what to say. I agree these things are important but somehow I feel I lack the big picture—having only enough of this picture to recognize that I lack it!
Perhaps others have more useful thoughts to add.
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