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The “Comprehensive R Archive Network” (CRAN) is a collection of sites which carry identical material, consisting of the R distribution(s), the contributed extensions, documentation for R, and binaries

he CRAN master site at TU Wien, Austria, can be found at the URL http://cran.R-project.org/ Daily mirrors are available at URLs including

R es un sistema para análisis estadísticos y gráficos creado por Ross Ihaka y Robert Gentleman

R tiene una naturaleza doble de programa y lenguaje de programación

R se distribuye gratuitamente bajo los términos de la GNU General Public Licence

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. Among other things it has 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 directly at the computer or on hardcopy, and a well developed, simple and effective programming language (called ‘S’) which includes conditionals, loops, user defined recursive functions and input and output facilities. (Indeed most of the system supplied functions are themselves written in the S language.)

R is a language and environment for statistical computing and graphics.

developed at Bell Laboratories

R provides an Open Source route to participation in that activity.

Incorporación de R en el mundo empresarial

El análisis de los grandes datos en forma de datos de medios sociales es un ejemplo

Si bien otro software de análisis puede realizar funciones similares, R le brinda un medio para explorar los datos de formas diferentes, rápidamente, en un entorno, luego compartirlo con otros de forma gráfic

Can I use R for commercial purposes?

R is released under the GNU General Public License (GPL) version 2. If you have any questions regarding the legality of using R in any particular situation you should bring it up with your legal counsel. We are in no position to offer legal advice. It is the opinion of the R Core Team that one can use R for commercial purposes (e.g., in business or in consulting). The GPL, like all Open Source licenses, permits all and any use of the package. It only restricts distribution of R or of other programs containing code from R. This is made clear in clause 6 (“No Discrimination Against Fields of Endeavor”) of the Open Source Definition:

R-statistics blog

around 245 active R bloggers 

What makes R particularly powerful is that statisticians and statistically minded people around the world have contributed packages to the R Group and maintain a very active news group offering suggestions and help. The growing collection of packages and the ease with which they interact with each other and the core R is perhaps the greatest advantage of R

Using R in 12 simple steps for personality research (These steps are not meant to limit what can be done with R, but merely to describe how to do the analysis for the most basic of research projects and to give a first experience with R). Install R on your computer or go to a machine that has it. Download the psych package as well as other recommended packages from CRAN using the install.packages function, or using the package installer in the GUI. To get packages recommended for a particular research field, use the ctv package to install a particular task view. Note, these first two steps need to be done only once! Activate the psych package or other desired packages using e.g., library(psych). This needs to be done every time you start R. Or, it is possible to modify the startup parameters for R so that certain libraries are loaded automatically. Enter your data using a text editor and save as a text file (perhaps comma delimited if using a spreadsheet program such as Excel or OpenOffice) Read the data file or copy and paste from the clipboard (using, e.g., read.clipboard). Find basic descriptive statistics (e.g., means, standard deviations, minimum and maxima) using describe. Prepare a simple descriptive graph (e.g, a box plot) of your variables. Find the correlation matrix to give an overview of relationships (if the number is not too great, a scatter plot matrix or SPLOM plot is very useful, this can be done with pairs.panels. If you have an experimental variable, do the appropriate multiple regression using stan- dardized or at least zero centered scores. If you want to do a factor analysis or principal components analysis, use the factanal or fa and principal function To score items and create a scale and find various reliability estimates, use score.items and perhaps omega. Graph the results.

R is statistical software which is used for data analysis.

It includes a huge number of statistical procedures such as t-test, chi-square tests, standard linear models, instrumental variables estimation, local polynomial regressions, etc. It also provides high-level graphics

capabilities