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What is R?

The Wikipedia page on the R Programming Language has a good overview, as does this overview from R Project website, but here's a summary of the key aspects of R.

R is data analysis software: data scientists, statisticians, analysts, quants, and others who need to make sense of data use R for statistical analysis, data visualization, and predictive modeling.

R is a programming language: you do data analysis in R by writing scripts and functions in the R programming language. R is a complete, interactive, object-oriented language: designed by statisticians, for statisticians. The language provides objects, operators and functions that make the process of exploring, modeling, and visualizing data a natural one. Complete data analyses can often be represented in just a few lines of code.

R is an environment for statistical analysis: Available in the R language are functions for virtually every data manipulation, statistical model, or chart that the data analyst could ever need. Not only are all the "standard" methods available, but because most cutting-edge research in statistics and predictive modeling is done in R, the latest techniques are usually available first in the R system.

R is an open-source software project. Not only does this mean that you can download and use R for free, but the source code is also open for inspection and modification to anyone who wants to see how the methods and algorithms work under the covers. Like other successful open-source projects such as Linux and MySQL, R has benefited for over 15 years from the "many-eyes" approach to code improvement, and as a result has an extremely high standard of quality and numerical accuracy. Also, as with all open-source systems R has open interfaces, meaning that it readily integrates with other applications and systems. 

R is a community. R was first created by Ross Ihaka and Robert Gentleman at the University of Auckland in 1993, and since then the project leadership has grown to include more than 20 leading statisticians and computer scientists from around the world. In addition, thousands of others have contributed additional functionality to the R language by creating add-on "packages" for use by the 2 million users of R worldwide. As a result, there is a strong and vibrant community of R users on-line, with a rich set of community-maintained resources for the beginning to the expert R user.

Next: Why use R?

This article has been translated to Serbo-Croatian by Jovana Milutinovich from webhostinggeeks.com