You can think of it as an environment within which statistical techniques are implemented and not as a statistics system. R environment is a fully planned and coherent integrated with software facilities for data manipulation, calculation and graphical display. Other software similar to R include SPSS, MATLAB, Mathematica, SAS, Julia, GNU Octave, PSPP, and more. It has hundreds of packages/libraries solely for analytics and it is fantastic for statical analysis. However, R has incredible data visualization and graphics capabilities. R can run slowly due to how data is stored and also cannot be embedded in web applications. It may be compared to the Python Programming language which is easier and maintain larger scale code as compared to R which might be difficult to maintain. Its well-designed charts, which are suitable for publishing, can make it simple to construct them, along with the necessary mathematical notation and formulas. It offers a wide range of statistical techniques, including time series analysis, classification, filtering, linear and non-linear modeling, traditional statistical tests, and more. It is free software that is released in source code form under the provisions of the GNU General Public License issued by the Free Software Foundation. It also functions as a statistical computing and graphical software environment. R is a programming language that can be built and executed on a variety of Unix platforms, macOS, and Windows. In this tutorial, we will look at how to Install and Use R and Rstudio on CentOS 9/ RHEL 9.
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