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Statistical Programming With R

Posted by timothy on from the no-r-in-statistics dept.

An anonymous reader writes "This series introduces you to R, a rich statistical environment, released as free software. It includes a programming language, an interactive shell, and extensive graphing capability. What's more, R comes with a spectacular collection of functions for mathematical and statistical manipulations -- with still more capabilities available in optional packages."

5 of 52 comments (clear)

  1. Graphing, hah! by Teancom · · Score: 4, Interesting

    We have a few people using R around here, mainly in the backend of cgis to produce graphs of various things. The main problem? If you want to output to a jpg or png (like, to display the result in a webpage), R has to create a window in X, draw onto the window, and then take a snapshot of the window. What this means on a headless sun machine? We get to run a virtual X server soley for our R cgis. Bloody hell, it's a stupid implementation of a crappy language.

    </cranky old man>

  2. Manipulations by Brandybuck · · Score: 4, Funny

    What's more, R comes with a spectacular collection of functions for mathematical and statistical manipulations...

    I can see that this package will be quite popular with political campaign managers.

    --
    Don't blame me, I didn't vote for either of them!
  3. what R isn't by bahamutirc · · Score: 5, Informative

    For people who have never taken real stat classes in college (or never learned it on their own) R will seem like a useless language. Most other languages can handle basic statistics computations.

    Statistics is a whole lot more than means and averages. When I took my first real stat class, everything I knew about statistics was literally covered on the first half of the first page. I was totally blown away by what you could do with statistics.

    R is for hardcore stat folk who know a bit about programming, not programmers who need to do a little basic computation.

  4. Re:So, what's the difference... by jeif1k · · Score: 4, Informative

    Octave differs substantially from Matlab and lacks a lot of functionality (in particular, a lot of the toolboxes). Octave is used for teaching, but most people who do serious work in Matlab use the real thing.

    In contrast, R is very close to Splus and comes with an extensive array of statistical toolboxes. Many professional users use, and even prefer, R for their day-to-day work.

    If you are doing anything with statistics, graphs of real-world data, or bioinformatics, R is the package to use.

    If you are doing other kind of numerical work, things are less clear. Matlab is widely used, but it is hugely expensive and the language is pretty limited. Octave is the obvious open source choice, but there aren't many packages for it, and Matlab software requires some amount of porting if you want to use it with Octave. Numerical Python is technically far better than either Matlab or Octave, and it has a lot of packages and features that neither offer, but it (obviously) isn't Matlab compatible, so you can't just load existing Matlab packages into it.

  5. RTFM! by KjetilK · · Score: 4, Informative
    As usual I strongly recommend RTFM, you don't need an X device to create bitmaps, but it is probably the simplest way to do it. With the modularity freedesktop is aiming for, this is probably become less and less of an argument, and probably the main reason why they haven't bothered rewriting it.

    R is really a beautiful language, for its purpose. It has a very nice correspondence with math and code, and for most parts of "hard" science, that's really important.

    Compared to MATLAB, you can easily write R code 5 times as compact as MATLAB code, and still get more understandable code.

    --
    Employee of Inrupt, Project Release Manager and Community Manager for Solid