"If our goal as a field is to use data to solve problems, then we need to move away from exclusive dependence on data models and adopt a more diverse set of tools."
Leo Breiman
Breiman ends the opening abstract of his "manifesto" to the statistical community with the above call to action. As a statistics professor at Berkeley, he was not an outsider.
Unfortunately, the warning was not heeded and now statistics laments with the President of the American Statistical Association asking "Aren't We Data Science?". Interestingly, one of the comments objects to a suggestion in this editorial that statisticians ought to learn R.
Clearly, someone has missed the point. It is not what you call yourself, who signs your paycheck, or the size of your data sets. It is your openness to disruptive innovation and your desire to make a difference. R provides the interface that makes this possible.
Breiman states it well at the end of an interview from 2001,
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.”
I would contend that modern data scientists are akin to jazz musicians. Applied research is part science and part art. We must have the skills to read and anticipate our audience, the facility to "play" with many instruments (e.g., R, SQL) and many rhythms (e.g., data mining, causal/structural models), and the disciplined creativity to blend it and share it well (visualization).
ReplyDeleteI would encourage you to look at the 2015 American Statistical Association Statement on the Role of Statistics in Data Science: magazine.amstat.org/blog/2015/10/01/asa-statement-on-the-role-of-statistics-in-data-science/
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