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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.
JASP (Jeffreys’s Amazing Statistics Program [2]) is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS .
R Commander (Rcmdr) is a GUI for the R programming language, licensed under the GNU General Public License, and developed and maintained by John Fox in the sociology department at McMaster University. [2] Rcmdr looks and works similarly to SPSS GUI by providing a menu of analytic and graphical methods. It also displays the underlying R code ...
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.
SuperCROSS – comprehensive statistics package with ad-hoc, cross tabulation analysis; Systat – general statistics package; The Unscrambler – free-to-try commercial multivariate analysis software for Windows; Unistat – general statistics package that can also work as Excel add-in; WarpPLS – statistics package used in structural ...
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 There were two reviews in journals (but not peer reviewed), one by Zhu and Kuljaca [26] and another article by Grant that included mainly a brief review of R. [27] Zhu and Kuljaca outlined some useful characteristics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.
Unlike analytics products offered by SAS Institute, R does not natively handle datasets larger than main memory.In 2010 Revolution Analytics introduced ScaleR, a package for Revolution R Enterprise designed to handle big data through a high-performance disk-based data store called XDF (not related to IBM's Extensible Data Format) and high performance computing across large clusters. [18]
RKWard aims to be easy to use, both for people with deep knowledge of R, and for users who, although they have experience in statistics, are not familiar with the language. The application design offers the possibility of using the graphic tools as well as ignoring many of them and using the program as integrated development environment .