Best programming languages for a statistician to know?

bryangoodrich

Probably A Mammal
#22
This question is ill-designed. There is no "best language" because the language is just a tool. That's like asking what is the best tool a carpenter can have on their belt. There may be a common tool they frequently use or one that can be used in a variety of settings, but rarely there is just one best tool. Instead, it's a question of the variety of things they can build with the tools they are capable of using, and what they are good at building depends on their interests. Some people want to do visual data exploration (R) and others want to work on parallel processing machine learning algorithms (Mahout). Some tools can be used in conjunction (I'm looking at you iPython notebooks! But we can even throw in SAS/IML calling R here).

The question would be better posed as "what tools should someone learning statistics today be comfortable with?" However, even this leaves it open to the analyst's interests. If you want to just do analysis, then a mix of SAS, R, Python (Numpy/Scipy/Scikit), Stata, or Matlab are good, but what if you want to be able to deploy an application that somebody can use? Then you need to learn something like Node.js, C#, Java, and so on. But today "Big Data" is both challenging and new, and there's a whole host of emerging technologies around it (namely, Hadoop and its ecosystem of Mahout, Hive, Pig, Tez).
 

noetsi

Fortran must die
#23
Leave it to byran to bring logic into this.....

What if your company only allows one language (or your boss did poorly in his one stats class and blames it all on R)?
 

bryangoodrich

Probably A Mammal
#24
GET A NEW COMPANY!

I use flexible tools that let me work with other tool sets. The hardest to work with is SAS, but one can also just learn the tools of their job. If I end up in a SAS shop, I'll learn SAS. But I'm thinking I need to just find a job that does what I want to do instead of being what my job needs me to be. It's my life and my future. If it don't fit, do better!

With that said, I'm with my job now until I finish the last 5k on my loans and get a car. Then I'm finding a place that lives R and Python!
 

noetsi

Fortran must die
#26
GET A NEW COMPANY!

I use flexible tools that let me work with other tool sets. The hardest to work with is SAS, but one can also just learn the tools of their job. If I end up in a SAS shop, I'll learn SAS. But I'm thinking I need to just find a job that does what I want to do instead of being what my job needs me to be. It's my life and my future. If it don't fit, do better!

With that said, I'm with my job now until I finish the last 5k on my loans and get a car. Then I'm finding a place that lives R and Python!
The practical problem with this, as someone involved recently in hiring a programmer is that you won't get hired in the first place commonly if you don't already have a specific skill set. Whether you have it or not is really not the question, you have to have it already on your resumee.
 

noetsi

Fortran must die
#27
I'd love to time that user implementing his problem in SAS.

Development time is often more valuable than computation time. Especially, if you work in the for-profit industry.
It would be useful to know what percent of the for profit industry uses R regularly (and not just looking at surveys of people who chose to respond to such questions, which won't be most businesses).
 

noetsi

Fortran must die
#29
That of course is the problem. Everyone only has their personal experiences. Mine suggests that R is never used in doing financial and statistical analysis (I worked in insurance and in state DOT and Education). I actually had to appeal public policy at one agency to get it allowed on the computer (the CIO refused to allow it on the computer initially).

Hedge funds using R is not really surprising. Many are as close to academic style analysis as you find in industry. Hey maybe the crash of 08 and the Great Recession that followed is all R's fault :mad: (It actually is the fault of a lot of arrogant economist and poor regulation of the industry).