November 23, 2015 Author: Matthew Renze

R is a statistical programming language that has become very popular in recent years for data analysis. Its interactive programming capabilities, powerful statistical analysis tools, and data visualization capabilities have made it the first choice of many data scientists, data analysts, and programmers for working with data.

R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand in 1993. It was based on the statistical programming language called S, which was invented at Bell Labs in 1976. R was open sourced in 1995 and has grown rapidly in popularity ever since.

R is both a language and an environment. This means that R provides us with both a programming language that we can use to write code and a development environment within which we can write that code.

R provides methods for both numerical and graphical data analysis. This means that we can work with data both numerically (e.g. calculating descriptive statistics) and graphically (e.g. creating data visualizations).

In addition, R is actively under development with new packages being created every day. It has a large and active user community. In addition, it is very modular and extensible. In fact, there currently exists over 6,700 extension packages for R.

Best of all, R is free open-source software. This means that R is both free, as in beer, meaning anyone can use R without cost. And free as in speech, meaning you can view the source code, learn from it, modify it or redistribute it as you wish.

If you want to learn more, please check out the following video:

If you have any questions, comments, or feedback, please let me know.

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