Group items tagged

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.

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 Library support; visualization Steep learning curve Yes Finance; Statistics

Matlab Elegant matrix support; visualization Expensive; incomplete statistics support No Engineering

This particular example would be really easy were we able to use RStudio’s manipulate package. That is only for RStudio users though. Well, not really. There is a simple map available in the gWidgetsWWW2.rapache package that allows us to easily use that specification

R es utilizado en google y faceboo

Es el nombre de un proyecto de código abierto consistente en un lenguaje de programación y un software de código abierto. Este software nos permite poder analizar datos de múltiples formas.

Es un software de uso común en departamentos de business intelligence dentro de las empresas, pero también es utilizado en investigación. 

Al tratarse de un software de código abierto, podemos decir que está vivo. La comunidad de R trabaja constantemente en desarrollar nuevas versiones mejoradas y en elaborar paquetes específicos para diferentes tipos de análisis. Así podemos encontrar paquetes de todo tipo (4293 a fecha de hoy), desde específicos para biólogos o genetistas, hasta modelos de hábitos de compra para marketing, pasando evidentemente por paquetes estadísticos de todo tipo y calidad.

Started as an open source programming language for data analysis, its popularity and use is spreading to major companies as diverse as Pfizer, Merck, Google, Shell, and Bank of America.

R programming language offers something that most of current languages do not support well, parallelism. With a package named “SNOW”, R can take advantage of multiple cores in the CPU. Due to the limitation in increasing CPU’s clock speed, Intel and AMD are stuffing more cores into the processors. There aren’t many software in the market that can take advantage of this, but R is.

R commander (Rcmdr)