ROI of Acquiring New Skills – GNU R as an Example

In his youtube video Courtney Brown , Ph.D. gives some reasons why learning R is worth the effort. His set of reasons is far from comprehensive but I think he covers some important aspects. In my opinion the return on investment argument is his most important one to convince people to learn R – especially potential business users and academics. The former are often dissatisfied with their current software (or its price),  the latter are often disillusioned by the non-applicability of many of their theoretical and software skills they acquired so far. Learning relevant methods and software to solve relevant problems is very satisfying. 

I’m not saying that solving highly theoretical problems — we quant-guys and -girls often have (and I believe should have) a strong inclination to — does not pay off at least intellectually towards improving problem solving and abstraction skills. But every professional researcher no matter if in science or business should – in my opinion – largely focus on a complete set of “Applicable-Right-Now-To-Solve-This-Real-World-Problem”-techniques to get relevant things done efficiently, effectively and correctly.  This will pay off intellectually and of course monetarily because people will pay you to solve their problems at hand. Since I learned to read mathbooks with a specific goal of application in my mind I understand even the most complex stuff much faster. This way you will become a professional in these skills who really deeply understands what he or she does. You will be able to apply complex methods (intellectually satisfying) to real world problems (monetarily satisfying) in a methodologically correct and thus very appealing way.

Unfortunately the value of the latter is often not recognized in business applications resulting in silly or simply wrong results. Even worse, attention ladies and gentlemen, putting (even unintentionally) wrong results on nicely designed PowerPoint slides does not make them correct. Therefore, I believe that every (wannabe) quant-guy or -girl cannot know enough math and theoretical background to avoid misapplication of methods. Customers should value this often painfully acquired knowledge and urge for correct and thus useful results. There are way too many people out there not caring about the correct application of methods with often fatal consequences, e.g. in medical research. But learning new methods and software should always be connected to solving real world, really relevant problems or improving your everyday work. With the output in mind you will be efficient and much more effective and motivated in acquiring new skills, however complex they are.

Here’s Mr. Brown’s video on why you should learn R (Hint: Don’t be deterred by the awful design of the video.):

Note: From the comments to this video we learn that PASCAL isn’t dead at all. For everyone interested in applying his or her knowledge of PASCAL see http://www.freepascal.org/.


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