I was intrigued by David Smith’s blog post at http://blog.revolutionanalytics.com/2013/08/job-trends-for-statistics-packages.html and played with some of the terms associated with analytics and data science.
Some points on that-
1) The term SAS is broader than the Statistical Software.
2) The term R is even broader. Accordingly I searched for R language- again it is a narrower term
3) Even by David’s own graph- SAS jobs have declined by 33% over two years, while R jobs have increased by 50%. However some jobs list both SAS and R so will be counted twice.
4) Even by David’s graph , SAS jobs are still twice as many as R jobs. So the overall market for analytics job is declined
5) I have no way to giving an exact conclusion unless I have access to the data, or I fire up a scraper myself.
6) Jobs remains a key area of concern for students and for future growth
7) Python statistical packages may need to be included shortly. I think sometimes it is easier to teach applied statistics (and data mining) to talented coders than teach scripting to talented statisticians.
8) Is hypothesis testing dead in the era of Big Data. What is a t test or chi square for a million rows. Almost all the better theory for such is locked in Bing or Google Research
9) The continued existence of Microsoft OS should be a sobering thought to people claiming ultimate victory too soon. Software needs to be sold, and sometimes the better sold software triumphs over the better designed software.
10) I would think that R has completely dominated the academic statistical market the same way SAS was doing it for business analytics some years back. However there exists much work to be done given some limitations of that software.
11) However SAS Institute revenue continues to grow. One reason for that could be the Institute work for big money clients including the US Government. Despite Drew Conway- I have yet to come across too many cases of the Big Fed using R.
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