Normal Deviate (thoughts on statistics and machine learning) is not a site I go to for the usual fare about project mangement, risk management, and the like, but with a provocative lead like "the death of statistics" I decided to read on...
As you might imagine, about the death of statistics we can say: Not exactly!
The issue seems to be all about the lastest meme, "big data" -- or in some quarters: "data science". With data warehouse projects and ERP projects, to say nothing of other "big science" projects (map the human brain?), project managers run into this stuff a lot. So, what is data analysis in the context of big data? What are we doing when we do data science?
These may not be the burning questions of the day, but we learn that Karl Broman -- who blogs at "The stupidest things -- statistics, genetics, programming, academics", is really wound up on this issue. He writes:
Of course, Mr Broman got some pushback from some of his readers. In particular, we saw this reply from Hillary Parker at "No so standard deviations":
When physicists do mathematics, they don’t say they’re doing “number science”. They’re doing math.
If you’re analyzing data, you’re doing statistics. You can call it data science or informatics or analytics or whatever, but it’s still statistics.
If you say that one kind of data analysis is statistics and another kind is not, you’re not allowing innovation.
"OK but… as you point out, physicists do mathematics, but still call themselves physicists because that’s not all they do.I guess I'm with Ms Parker on this one... project managers do statistics (or get their project analysts to do stastistics for them) but still call themselves PMs or analysts....
Whether or not you agree, data scientists would qualify themselves the same way — they do statistics, but also other things that statisticians generally do not do (product development, system administration, engineering, etc.).
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