- 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. 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. This programming language was named **R**, based on the first letter of first name of the two R authors (Robert Gentleman and Ross Ihaka), and partly a play on the name of the Bell Labs Language **S**.

This tutorial is designed for software programmers, statisticians and data miners who are looking forward for developing statistical software using R programming. If you are trying to understand the R programming language as a beginner, this tutorial will give you enough understanding on almost all the concepts of the language from where you can take yourself to higher levels of expertise.

Before proceeding with this tutorial, you should have a basic understanding of Computer Programming terminologies. A basic understanding of any of the programming languages will help you in understanding the R programming concepts and move fast on the learning track.

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