R programming language gaining ground on Conventional statistics packages


The R programming language is quickly gaining popular ground against the conventional data packages such as SPSS, SAS and MATLAB, at least based on one data statistician who instructs the language.

“It is extremely probable that throughout the summer of 2014, R became the most commonly used analytics software for scholarly articles, ending a spectacular 16-year run by SPSS,” wrote Robert Muenchen, in a blog post summarizing his analysis.

Muenchen gauged the popularity of statistical software packages by monitoring how often they’ve been employed for published scientific research and the number of references that they get in internet discussion forums, blogs, job listings and other sources.

Scholarly citations are a “good leading indicator of where things are headed,” Muenchen wrote. Students who learn to use these software packages later go on to use them in their professional careers, either in academia or business.

In his most recent survey, Muenchen found that investigators continue to do most of their work on conventional software packages, namely SAS’s and MATLAB’s self-named bundle, as well as IBM’s SPSS.

R is an open-source functional programming language constructed for statistical computing and graphics .

Muenchen, a certified statistician who manages the research computing support at the University of Tennessee, might not be the most unbiased individual to announce a success for R–he also works as an R instructor on behalf of Revolution Analytics. But he has also been long recognized as an authority in computer analytics, leading code into SAS, SPSS and assorted R packages. He’s also served on the advisory boards of SAS and SPSS before it was acquired by IBM in 2009.

Muenchen did not speculate in the blog article summarizing his findings concerning the reason why R is gaining popularity.

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R programming language gaining ground on Conventional statistics packages

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