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R

R

The R Project for Statistical Computing (R) is a free software environment for statistical computing and graphics.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.

The S language is often the vehicle of choice for research in statistical methodology, and econometrics, and R provides an Open Source route to participation in that activity.

 R 3.2.0

Price
Free to download

Size
27.8MB
License

GNU GPL v2

Developer
R Development Core Team

Website
www.r-project.org

System Requirements

Support:
R ManualsFAQ
, Newsletter, Mailing List, Kickstarting R, Journal of Statistical Software, Technical Notes on the R programming language, R_note, R Tips, Using R for Psychology Research

Selected Reviews:
Sciviews.org, dmreview, Statland.org

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes:

  • An effective data handling and storage facility,
  • A suite of operators for calculations on arrays, in particular matrices,
  • A large, coherent, integrated collection of intermediate tools for data analysis
  • Graphical facilities for data analysis and display either on-screen or on hardcopy, and
  • A well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

One of R's strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.

R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made.

Although R is mostly used by statisticians who need an environment for statistical computation and software development, it can also be used as a general matrix calculation toolbox with comparable benchmark results to Octave and its proprietary counterpart, MATLAB (version < 7).

There are a number of excellent graphical frontends for R. You can view our favourites at 7 of the Best Free Graphical User Interfaces for R.

Return to Scientific Home Page | Return to Econometric Home Page | Return to Data Mining Home Page | Return to Statistical Analysis Home Page

R also features in our 'Linux Equivalents to Windows Software' section. The category selector below allows you to filter the different types of software included in that separate article.

Category:

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Last Updated Monday, May 18 2015 @ 03:38 PM EDT


We have written a range of guides highlighting excellent free books for popular programming languages. Check out the following guides: C, C++, C#, Java, JavaScript, CoffeeScript, HTML, Python, Ruby, Perl, Haskell, PHP, Lisp, R, Prolog, Scala, Scheme, Forth, SQL, Node.js (new), Fortran (new), Erlang (new), Pascal (new), and Ada (new).


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