Getting Started with R Programming
The R environment
R is an integrated suite of software facilities for data manipulation, calculation and graphical display. Among other things it has * an effective data handling and storage facility, * a suite of operators for calculations on arrays, in particular matrices, * a large, coherent, integrated collection of intermediate tools for data analysis, * graphical facilities for data analysis and display either directly at the computer or on hardcopy, and * a well developed, simple and effective programming language (called ‘S’) which includes conditionals, loops, user defined recursive functions and input and output facilities. (Indeed most of the system supplied functions are themselves written in the S language.)
The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software. R is very much a vehicle for newly developing methods of interactive data analysis. It has developed rapidly, and has been extended by a large collection of packages. However, most programs written in R are essentially ephemeral, written for a single piece of data analysis. (Source: An Introduction to R - R Help)
- The Comprehensive R Archive Network: https://cran.r-project.org/ and
- Microsoft R Open (MRO): The Enhanced R Distribution is here https://mran.microsoft.com/open/.
Microsoft R Open, formerly known as Revolution R Open (RRO), is the enhanced distribution of R from Microsoft Corporation. It is a complete open source platform for statistical analysis and data science.
The current version, Microsoft R Open 3.3.*, is based on (and 100% compatible with) R-3.3.1, the most widely used statistics software in the world, and is therefore fully compatibility with all packages, scripts and applications that work with that version ofR. It includes additional capabilities for improved performance, reproducibility, as well as support for Windows and Linux-based platforms.
Like R, Microsoft R Open is open source and free to download, use, and share.
Read complete article here.
I have tried to put together necessary links and resources to help you start learning R quickly.
This article is developed on R Markdown and published on RPubs. You may access the article here https://rpubs.com/arifulmondal/startR