R 3.2.0

Provides quick access to a language that enables you to perform the statistical analysis of various types of data and generate graphics for the results.

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What's new in R 3.2.0:

  • anyNA() gains a recursive argument.
  • When x is missing and names is not false (including the default value), Sys.getenv(x, names) returns an object of class "Dlist" and hence prints tidily.
  • (Windows.) shell() no longer consults the environment variable SHELL: too many systems have been encountered where it was set incorrectly (usually to a path where software was compiled, not where it was installed). R_SHELL, the preferred way to select a non-default shell, can be used instead.
  • Some unusual arguments to embedFonts() can now be specified as character vectors, and the defaults have been changed accordingly.
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LICENSE TYPE:
GPL 
FILE SIZE:
70.2 MB
OUR RATING:
4.0/5
DEVELOPED BY:
R Project
USER RATING:
2.8/5 28
CATEGORY:
Home \ Math/Scientific
10 R Screenshots:
R - By accessing the main window of the application, you will be able to read some information about the R environment.R - From the Workspace menu you can access the Workspace browser as well as display the current workplace.R - From the packages and data menu you can access the package manager and installer, as well as data manager.RRRRRRR
Inspired by the S statistical programming language developed at the Bell Laboratories, the R language can be used to perform computer statistical analysis for all sorts of information. At the same time, you can also use its capabilities to generate relevant graphics.

Easy to install binaries

The source code for the R language is publicly available, but the precompiled binary distributions represent a more intuitive manner of getting in contact with everything the R project has to offer.

The R installer package will guide you through the entire process and you will be able to use R via a simple, organized user interface that resembles a word processor. The best part is that the R installer contains all the required components, such as the R Framework, the R.app GUI and Tcl/Tk for X11.

Various tools for statistical analysis

You can use the R language to perform different types of statistical calculations for linear and non-linear modeling, classical statistical tests, classifications, clustering, time series analysis, and more. Moreover, R provides support for various graphical techniques and you can choose to display the result on the screen or send it to the printer.

The R operators can be used to perform calculations in matrices or arrays, while the programming language also allows you to set up different conditionals, recursive functions, loops and more.

User friendly user interface

Most of the R capabilities can be accessed via the R Console which is represented by a simple and well organized window. The main area is reserved for displaying the code and the results, while the top toolbar includes buttons for frequently used tools.

Of course, the R Console menus also include useful options: you can switch between workspaces, access the package manager / installer, reset the working directory and more.

Useful programing language for processing statistical data

The R project is providing quick access to a programming language that can be used to make statistical computations and generate graphical representations. The best part is that the language can be accessed via an user friendly GUI.

R was reviewed by , last updated on April 20th, 2015

Runs on: Mac OS X 10.6 or later (Intel only)

requirements

#statistics environment #time-series analysis #computing environment #statistics #computing #analyzer #analysis

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