Beginning R: The Statistical Programming Language by Mark Gardener

Beginning R: The Statistical Programming Language



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Beginning R: The Statistical Programming Language Mark Gardener ebook
ISBN: 9781118164303
Publisher: Wrox Press, Inc.
Page: 504
Format: pdf


Here we go for a Vector Computing Comparison: R Language vs. Here is the data from Google Scholar: R SAS SPSS Stata 1995 7 9120 7310 24 1996 4 9130 8560 92 1997 Professors looking to meet student demand for greater ease of use are not sure which GUI to teach, so they continue teaching SAS as a programming language. The R programming language is an open-source, interactive language that was designed for manipulating datasets, creating visualizations, and performing statistical analyses. To me, one of the most attractive features of R language and esProc is that their codes are both agile, that is, only requiring a few lines of codes to implement plentiful functions. Begin by starting the R environment. John Chambers has been the principal designer of the S language since its beginning, and in 1999 received the ACM System Software award for S, the only statistical software to receive this award. R is (according to the description at http://www.r-project.org/) "a language and environment for statistical computing and graphics"; you can think of it as a combination of a statistics package and a programming language. Building R packages is not particular hard, but it can be a bit of a daunting endeavour at the beginning, particularly if you are more of a statistician than a computer scientist or programmer. Kick off your Memorial Day long weekend with a Polyglot Programmers meetup on Thursday, May 23. Let's take a more detailed look at what the future may hold for R, SAS and SPSS Statistics. Personally, I think SAS is a wonderful application, with my SAS experience starting in SAS programming back in 1989 (mainframes, along with Fortran), SAS Enterprise Guide (I wrote SAS for Dummies, the first two editions with Chris Here's my original comments on Bob's nice review of the growth of various statistical tools:While R-Studio looks like a beautiful IDE, it isn't a GUI application for business analysts who won't/can't invest in learning R as a language. R is still undeniably a niche language, with 0.609% of the ratings (compared to 17.479% for Java or 3.218% for Python). Do you find Vector Computing tiresome while using statistical computing tools?





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