R Programming gives a broad variety of statistical (direct and nonlinear modeling), traditional statistical tests, time-arrangement analysis, grouping, bunching and graphical techniques, and is profoundly extensible. The S language is regularly the vehicle of decision for exploration in statistical methodology, and R gives an Open Source route to cooperation in that action.

R Programming applications compass the universe from hypothetical, computational statistics and the hard sciences, for example, astronomy, chemistry, and genomics to practical applications in business, drug advancement, finance, health care, marketing, medicine and much more. Since R has almost 5,000 packages (libraries of functions) large portions of which are committed to particular applications, you don't need to be an R Programming genius to begin developing your applications.