- R Tutorial
- R - Home
- R - Overview
- R - Environment Setup
- R - Basic Syntax
- R - Data Types
- R - Variables
- R - Operators
- R - Decision Making
- R - Loops
- R - Functions
- R - Strings
- R - Vectors
- R - Lists
- R - Matrices
- R - Arrays
- R - Factors
- R - Data Frames
- R - Packages
- R - Data Reshaping

- R Data Interfaces
- R - CSV Files
- R - Excel Files
- R - Binary Files
- R - XML Files
- R - JSON Files
- R - Web Data
- R - Database

- R Charts & Graphs
- R - Pie Charts
- R - Bar Charts
- R - Boxplots
- R - Histograms
- R - Line Graphs
- R - Scatterplots

- R Statistics Examples
- R - Mean, Median & Mode
- R - Linear Regression
- R - Multiple Regression
- R - Logistic Regression
- R - Normal Distribution
- R - Binomial Distribution
- R - Poisson Regression
- R - Analysis of Covariance
- R - Time Series Analysis
- R - Nonlinear Least Square
- R - Decision Tree
- R - Random Forest
- R - Survival Analysis
- R - Chi Square Tests

- R Useful Resources
- R - Interview Questions
- R - Quick Guide
- R - Useful Resources
- R - Discussion

R is a programming language and software environment for statistical analysis, graphics representation and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team.

The core of R is an interpreted computer language which allows branching and looping as well as modular programming using functions. R allows integration with the procedures written in the C, C++, .Net, Python or FORTRAN languages for efficiency.

R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows and Mac.

R is free software distributed under a GNU-style copy left, and an official part of the GNU project called **GNU S**.

R was initially written by **Ross Ihaka** and **Robert Gentleman** at the Department of Statistics of the University of Auckland in Auckland, New Zealand. R made its first appearance in 1993.

A large group of individuals has contributed to R by sending code and bug reports.

Since mid-1997 there has been a core group (the "R Core Team") who can modify the R source code archive.

As stated earlier, R is a programming language and software environment for statistical analysis, graphics representation and reporting. The following are the important features of R −

R is a well-developed, simple and effective programming language which includes conditionals, loops, user defined recursive functions and input and output facilities.

R has an effective data handling and storage facility,

R provides a suite of operators for calculations on arrays, lists, vectors and matrices.

R provides a large, coherent and integrated collection of tools for data analysis.

R provides graphical facilities for data analysis and display either directly at the computer or printing at the papers.

As a conclusion, R is worldâ€™s most widely used statistics programming language. It's the # 1 choice of data scientists and supported by a vibrant and talented community of contributors. R is taught in universities and deployed in mission critical business applications. This tutorial will teach you R programming along with suitable examples in simple and easy steps.

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