‘R’ is free open source statistical analysis software. It is a full-fledged programming language intended to process large and complex datasets. R compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. Though mostly used in research, academic, and development environments, R is gradually growing in usability in commercial environments with the increasingly focus on data driven businesses and data analytics.
As R is heading into mainstream, the skill is getting very popular among data scientists, statisticians and analytics professionals. As per the Dice Tech salary survey, R is one of the top paid IT skills in 2014.
If this sounds interesting, you may want to invest time to play around with it. Here are the five web resources that you can use.
- http://tryr.codeschool.com/ – Try codeschool to jumpstart R without the hassle of any installation or setup.
- http://www.johndcook.com/R_language_for_programmers.html – very good introductory tutorial from John Cook.
- http://blog.revolutionanalytics.com/2012/12/coursera-videos.html – R video tutorial from Coursera
- http://www.r-project.org/ – Official R-Project website for latest updates and references
- Getting Started with the R Data Analysis Package By Norm Matloff
One of the main reasons of growing popularity of R is it offers benefits to companies trying to reduce their software expenditures with enterprise software vendors such as SAS and SPSS. With the increasing demand, analytic professionals, data miners and aspiring data scientists can make a very good move by adding the important R-skillset into their arsenal.
References / Further read