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R first appeared in 1996, when the statistics professors Robert Gentleman, left, and Ross Ihaka released the code as a free software package.

By ASHLEE VANCE
Published: January 6, 2009

To some people R is just the 18th letter of the alphabet. To others, it’s the rating on racy movies, a measure of an attic’s insulation or what pirates in movies say.

R is also the name of a popular programming language used by a growing number of data analysts inside corporations and academia. It is becoming their lingua franca partly because data mining has entered a golden age, whether being used to set ad prices, find new drugs more quickly or fine-tune financial models. Companies as diverse as Google, Pfizer, Merck, Bank of America, the InterContinental Hotels Group and Shell use it.

But R has also quickly found a following because statisticians, engineers and scientists without computer programming skills find it easy to use.

“R is really important to the point that it’s hard to overvalue it,” said Daryl Pregibon, a research scientist at Google, which uses the software widely. “It allows statisticians to do very intricate and complicated analyses without knowing the blood and guts of computing systems.”

It is also free. R is an open-source program, and its popularity reflects a shift in the type of software used inside corporations. Open-source software is free for anyone to use and modify. I.B.M., Hewlett-Packard and Dell make billions of dollars a year selling servers that run the open-source Linux operating system, which competes with Windows from Microsoft. Most Web sites are displayed using an open-source application called Apache, and companies increasingly rely on the open-source MySQL database to store their critical information. Many people view the end results of all this technology via the Firefox Web browser, also open-source software.

R is similar to other programming languages, like C, Java and Perl, in that it helps people perform a wide variety of computing tasks by giving them access to various commands. For statisticians, however, R is particularly useful because it contains a number of built-in mechanisms for organizing data, running calculations on the information and creating graphical representations of data sets.

Some people familiar with R describe it as a supercharged version of Microsoft’s Excel spreadsheet software that can help illuminate data trends more clearly than is possible by entering information into rows and columns.

What makes R so useful — and helps explain its quick acceptance — is that statisticians, engineers and scientists can improve the software’s code or write variations for specific tasks. Packages written for R add advanced algorithms, colored and textured graphs and mining techniques to dig deeper into databases.

Close to 1,600 different packages reside on just one of the many Web sites devoted to R, and the number of packages has grown exponentially. One package, called BiodiversityR, offers a graphical interface aimed at making calculations of environmental trends easier.

Another package, called Emu, analyzes speech patterns, while GenABEL is used to study the human genome.

The financial services community has demonstrated a particular affinity for R; dozens of packages exist for derivatives analysis alone.

“The great beauty of R is that you can modify it to do all sorts of things,” said Hal Varian, chief economist at Google. “And you have a lot of prepackaged stuff that’s already available, so you’re standing on the shoulders of giants.”

R first appeared in 1996, when the statistics professors Ross Ihaka and Robert Gentleman of the University of Auckland in New Zealand released the code as a free software package.

Full article at: http://www.nytimes.com/2009/01/07/technology/business-computing/07program.html?_r=1&em

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