Key Features and Applications
Some key features of R that make the R one of the most demanding job in data science market are:
- Basic Statistics: The most common basic statistics terms are the mean, mode, and median. These are all known as “Measures of Central Tendency.” So using the R language we can measure central tendency very easily.
- Static graphics: R is rich with facilities for creating and developing various kinds of static graphics including graphic maps, mosaic plots, biplots, and the list goes on.
- Probability distributions: Using R we can easily handle various types of probability distribution such as Binomial Distribution, Normal Distribution, Chi-squared Distribution, and many more.
- R Packages: One of the major features of R is it has a wide availability of libraries. R has CRAN(Comprehensive R Archive Network), which is a repository holding more than 10,0000 packages.
- Distributed Computing: Distributed computing is a model in which components of a software system are shared among multiple computers to improve efficiency and performance. Two new packages ddR and multidplyr used for distributed programming in R were released in November 2015.
Applications of R
Learn R Programming
R is a Programming Language that is mostly used for machine learning, data analysis, and statistical computing. It is an interpreted language and is platform independent that means it can be used on platforms like Windows, Linux, and macOS.
In this R Language tutorial, we will Learn R Programming Language from scratch to advance and this tutorial is suitable for both beginners and experienced developers).
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