R is an excellent programming language for statistics or data analysis and it has at the top a list of big users, the biggest of them being Google. The language is appreciated because of the power it offers to the mathematicians of the company.
R is a system for statistical and graphical analysis created by Ross Ihakasi and Robert Gentleman. It is equally software and programming language considered to be a dialect of the S language created by AT&T Bell Laboratories.
There are important differences between R and S design.
R is freely distributed under the GNU General Public License, and its development and distribution are in the care of a few statisticians known as the R Development Core Team.
R is available in several forms: sources (developed especially in C and Fortran procedures), essential for Unix and Linux or a few predefined binary files for Windows, Linux, and Macintosh. The necessary files for installing R, either from sources or from predefined binary files, are distributed on the Comprehensive R Archive Network (CRAN) website where installation instructions are also found.
As for Linux variants (Debian, CentOS), Binary files are generally available for most versions.
R has many functions for statistical and graphical analysis; recent ones have instant view in their own window and can be saved in different formats (jpg, png, bmp, ps, pdf, emf, pictex, xfig) the available formats may depend on the operating system.
The results of a statistical analysis are displayed on the screen, some intermediate results (probabilities, regression coefficients, residual values) can be saved, written in a file, or used in subsequent analyzes.
The R language allows the user, for example, to program instruction groups for successive analysis of data sets.
It is also possible to combine several statistical functions in a single program to perform more complex analyzes.
R users can benefit from a wide range of programs made for S and available on the Internet, most of which can be used directly in R.
At first glance, R may seem too complex for a non-specialist, but the things are not so complicated as they seem.
In fact, an important feature of R is its flexibility.
While classical software immediately displays the results of an analysis, R stores these results in an “object”, so that an analysis can be performed without displaying any results. The user may be surprised by this, but such a feature is very useful. Indeed, the user can only extract the part of the result he is interested in.
For example, if someone runs a series of 20 regressions and wants to compare different regression coefficients, R can display only the estimated coefficients: thus the result can have a single line, while a classic software can open 20 windows with results.
R is an interpreted language, not a compiled one, which means that all the commands entered through the keyboard are directly executed without the need to write a complete program as it happens in most programming languages.
Syntax R is very simple and intuitive.
In R, to be able to execute, a function must always be written in parentheses, even if there is nothing written between them (for example, ls ()). If you type the name of a function without being followed by parentheses, R will display the content of the function.