"... academic statistics may have lost its way."
See my previous post on the statistician Leo Breiman, and his background
in consulting for industry : http://asterisk.dynevor.org/industry-as-the-origin.html
Breiman talked about data analysis in industry and academia in an interview with his colleague Richard Olshen:
"Olshen: ... What advice would you give to a young person today who wants to continue in your traditions? What should he or she study and why?
Breiman: Well Richard, I’m torn in a way because what I might even tell them is, “Don’t go into statistics.” My feeling is, to some extent, that academic statistics may have lost its way. When I came, after consulting, back to the Berkeley Department, I felt like I was almost entering Alice in Wonderland. That is, I knew what was going on out in industry and government in terms of uses of statistics, but what was going on in academic research seemed light years away. It was proceeding as though it were some branch of abstract mathematics. One of our senior faculty members said a while back, “We have to keep alive the spirit of Wald.” But before the good old days of Wald and the divorce of statistics from data, there were the good old days of Fisher, who believed that statistics existed for the purposes of prediction and explanation and working with data.Before you came this morning, I pulled out Webster’s dictionary and looked for the definition of statistics, and here is how it goes: “Statistics, facts or data of the numerical kind assembled, classified, and tabulated so as to present significant information about a given subject.” When used with a singular verb, it is, quote, “The science of the assembling, classifying, tabulating, and analyzing such facts or data.”
Now, little of that is going on in the academic world of statistics. For instance, I was looking at The Annals of Statistics and I estimate that maybe 1 paper in 20 had any data in it or applied the methods there to any kind of data. The ratio is not much higher in the Journal of the American Statistical Association. So my view of what’s fascinating in the subject of statistics and the common academic view are pretty far apart.
In the past five or six years, I’ve become close to the people in the machine learning and neural nets areas because they are doing important applied work on big, tough prediction problems. They’re data oriented and what they are doing corresponds exactly to Webster’s definition of statistics, but almost none of them are statisticians by training.
So I think if I were advising a young person today, I would have some reservations about advising him or her to go into statistics, but probably, in the end, I would say, “Take statistics, but remember that the great adventure of statistics is in gathering and using data to solve interesting and important real
world problems.
Right at the end of the interview:
You know, sometimes I feel sad about statistics.There are so many smart people in it and I hope it gets better before it gets worse.
Richard Olshen (2001) "A conversation with Leo Breiman" Statistical
Science
16(2): 184–198. http://projecteuclid.org/download/pdf_1/euclid.ss/1009213290
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