R Software For Data Analysis: R is a programming language and free software developed by Ross Ihaka and Robert Gentleman (1993) from the University of Auckland, New Zealand. R is a language and environment for statistical computing and graphics. The R language is widely used by statisticians for developing statistical software and data analysis. The source code of R is maintained by a group called the R development Core Team and it is freely distributed under the terms of the GNU General Public Licence. R allows integration with the procedures written in the C, C++, Net, or FORTRAN languages for efficiency. Pre-compiled binary versions of R are provided for various operating systems link Linux, Windows, and Macintosh. R is both a software and a language considered as a dialect of the S language created by Bell Laboratories, S is available as the software S-PLUS commercialized by Insightful.
Data analysis with ‘R’ is useful for programming, transforming, discovering, modeling, and communicating the results. It is an accessible programming tool and made up of a collection of libraries designed specifically for data science. It is used to investigate the data, refine the hypothesis, and provide a wide array of tools to capture the right model for data analysis, R markdown, or build shiny apps to share integrated codes, graphs, and outputs of the report to everyone.
‘R’ may be installed from the sources or the pre-compiled binaries. They are distributed from the internet site of the Comprehensive R Archive Network (CRAN), https: cran.r_project.org/. The site also contains documentation for downloading and installing the software on different operating systems. R may visualize immediately in their window and can be saved in jpg, png, bmp, pdf, pictex, etc. The results from statistical analysis are displayed on the screen as p-values, regression coefficients, residuals, etc.
The download package and installed from the CRAN mirror contains R language and a user interface called the RGui. ‘RGui’ is a short form for ‘R Graphical User Interface and it is an easy way to interact with R language. Like other similar languages such as APL and MATLAB, R supports matrix arithmetic. R’s data structures include vectors, matrices, arrays, data frames, and lists. The capabilities of R are extended through user-created packages, which allow specialized statistical techniques, graphical devices, reporting tools, etc.
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