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The Comprehensive R Archive Network (CRAN) homepage The Comprehensive R Archive Network (CRAN) is R's central software repository , supported by the R Foundation. [ 9 ] It contains an archive of the latest and previous versions of the R distribution, documentation, and contributed R packages. [ 10 ]
R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics and data analysis. [9] The core R language is augmented by a large number of extension packages, containing reusable code, documentation, and sample data. R software is open-source and free software.
The RStudio CRAN mirror download logs [11] show that the package is downloaded on average about 2,000 per month from those servers , [12] with a total of over 100,000 downloads since the first release, [13] according to RDocumentation.org, this puts the package in the 15th percentile of most popular R packages .
RStudio IDE (or RStudio) is an integrated development environment for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
For the R programming language, the Comprehensive R Archive Network (CRAN) runs tests routinely. To understand how this is valuable, imagine a situation with two developers, Sally and John. Sally contributes a package A. Sally only runs the current version of the software under one version of Microsoft Windows, and has only tested it in that ...
cran.r-project.org /web /packages /qdap / Quantitative Discourse Analysis Package (qdap) is an R package for computer assisted qualitative data analysis , particularly quantitative discourse analysis , transcript analysis and natural language processing .
DMAIC and Lean online project collaboration tools for local and global teams; Data Collection tools that feed information directly into the analysis tools and significantly reduce the time spent gathering data.
There are a few reviews of free statistical software. There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics of software, such as ease of use, having a number of statistical procedures and ability to develop new procedures.