- R - Data Reshaping
- R - Packages
- R - Data Frames
- R - Factors
- R - Arrays
- R - Matrices
- R - Lists
- R - Vectors
- R - Strings
- R - Functions
- R - Loops
- R - Decision Making
- R - Operators
- R - Variables
- R - Data Types
- R - Basic Syntax
- R - Environment Setup
- R - Overview
- R - Home
R Data Interfaces
- R - Database
- R - Web Data
- R - JSON Files
- R - XML Files
- R - Binary Files
- R - Excel Files
- R - CSV Files
R Charts & Graphs
R Statistics Examples
- R - Chi Square Tests
- R - Survival Analysis
- R - Random Forest
- R - Decision Tree
- R - Nonlinear Least Square
- R - Time Series Analysis
- R - Analysis of Covariance
- R - Poisson Regression
- R - Binomial Distribution
- R - Normal Distribution
- R - Logistic Regression
- R - Multiple Regression
- R - Linear Regression
- R - Mean, Median & Mode
R Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
R Tutorial
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 Pubpc License, and pre-compiled binary versions are provided for various operating systems pke 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.
Audience
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.
Prerequisites
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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