*First steps in R* does not pretend to be a comprehensive guide to R package
(there are many excellent books and web tutorials) but it aims at providing an
introduction to the R statistical package for the (under)graduate students
following an introductory Statistics Course.

*************
Introduction
*************

.. _intro:

**Why R?** 

Although there are many tools that can be employed for statistical
analysis (SAS, SPSS, Stata, Minitab, MATLAB, Wolfram Mathematica,... among
others), we have chosen R because:

* It is an **integrated environment**: it has been developed as a whole entity and not as a collection of tools. It includes:

  * An efficient system for data storage and manipulation

  * A collection of tools to manage arrays
  
  * Integrated tools for data analysis

  * Screen graphs and portable format graphs generation 
  
  * A simple and effective programming language (with *scripting* capabilities)

* It is **free software**! Available through the `project WEB <http://www.r-project.org>`_ or through `CRAN <http://cran.r-project.org>`_ (*Comprehensive R Archive Network*)

* Available for **different platforms** (source code and pre-compiled binaries): :t:`UNIX`, :t:`MacOS`, :t:`Windows`

* ...

* Many scientists are using it!

.. image:: images/hpgraphic.png
    :scale: 70 %
    :align: center

(*image from* `R project web page <http://www.r-project.org>`_)

**R** is continuously (and exponentially) growing with the addition of contributed packages.

.. image:: images/exponential-growth.png
    :scale: 80 %
    :align: center

(*from* `R Journal <http://journal.r-project.org/archive/2009-2/>`_)

Although... No statistical package can work miracles!

(**GIGO**: Garbage In, Garbage Out)

.. image:: images/garbageinout.png
    :align: center

(*image from* http://www.lovemytool.com)