R tutorial

2010-01-26T20:31:00.000-08:00

Introduction to R

R is an open source statistical package for statistical computing and graphics. It was developed at Bell Laboratories by John Chambers and colleagues. The package is based on S language and most of the codes in S language run in R. It is a GNU project and the package is freely available to download at http://www.r-project.org/index.html. R is well known for its powerful capabilities on producing publication quality graphs.

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

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 on-screen or on hardcopy, and
a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.

R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.

Source: www.r-project.org

Downloading R

To download R package, click here. There are three versions of R available to download. Click the one you needed. This tutorial explains the procedure to download R for Windows.

Click Windows

Click base

Click R-2.7.2-win32.exe

Run the program to install R in your system. You can also download R from the nearest mirror site to your area. Click here to find the nearest mirror.

What is R?

2008-06-14T10:22:00.000-07:00

What is R?

R is a software package especially suitable for data analysis and graphical representation. Functions and results of analysis are all stored as objects, allowing easy function modification and model building. R provides the language, tool, and environment in one convenient package.
It is very flexible and highly customizable. Excellent graphical tools make R an ideal environment for EDA (Exploratory Data Analysis). Since most high level functions are written in R language itself, you can learn the language by studying the function code.
On the other hand, R has a few weaknesses. For example, R is not particularly efficient in handling large data sets. Also, it is rather slow in executing a large number of for loops, compared to compiler languages such as C/C++. Learning curve is somewhat steep compared to "point and click" software.

R

2008-03-24T14:05:00.001-07:00

Welcome to the world of R

A comprehensive tutorial for R

R tutorial

What is R?

R