**What is R?**

R is a programming language and software environment for statistical computing and graphics supported by the R Foundation for Statistical Computing. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories by John Chambers and colleagues. R can be considered as a different implementation of S.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems, Windows and MacOS.

**The R environment** -

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

- an effective data handling and storage facility,
- a suite of operators for calculations on arrays, in particular matrices,
- a large, coherent, integrated collection of intermediate tools for data analysis,
- graphical facilities for data analysis and display either on-screen or on hardcopy, and
- a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

**Reasons to learn R -**

**1. R is freely available -** Unlike SAS or Matlab, you can freely “install, use, update, clone, modify, redistribute, and even resell” R.

**2. R has widespread acclaim -** Given all these benefits, it’s not surprising that R is gaining wide-spread acclaim – it is estimated that it has about 2 million users, and a recent poll suggests that it is the most popular language in data science.

**3. R is a heavy-duty language -** As a powerful scripting language, R will help you handle large, complex data sets. It is a great programming language to compute Big Data. R is also the best language to use for heavy, resource intensive simulations. Furthermore, R can be used on high performance computer clusters which manage the processing capacity of huge numbers of processors.

**4. R leads innovations in statistics -** Many new developments in statistics first appear as R packages. This is because R is highly flexible and evolved.

**5. Language integrate -** Need to run statistical calculations in your software application?? Deploy R! It integrates with many programming languages like Java, Ruby, C++, Python

**6. R is loved by publishers -** R is a language that integrates easily with document publishing. By integrating smoothly with the LaTeX document publishing system, statistical output and graphics from R can be embedded in word-processing documents.

**7. Reusable libraries -** R has 2000+ free libraries to use in areas of finance, natural language processing, cluster analysis, optimization, prediction, high performance computing etc.

**8. No Windows, No Doors –** R runs on all the platforms. Just name it and you got it!! Windows PC, Mac, Linux.

**9. Used by many popular companies -** Leading firms like NY Times, Google, Facebook, Bank of America, Pfizer, Merck are all using R.

**10. IT demand -** Want the coolest job in 2017?? Learn Statistics. It is the future. Data Scientists will be the sexy job in 2018.