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=Extension: Using R, statistical and graphics software.=

== Introduction ==
This appendix introduces the reader to R. It is for those course participants who do a substantial amount of statistical analyses (or aim to) and wish to improve their capability beyond what Excel allows. There may not be time to complete this appendix during the course, but it can be completed later.

R is a statistical and graphics software environment. It is widely recognised and used throughout the world. R provides a very powerful and flexible environment in which to conduct simple or complex statistics or to produce publication ready graphics. It is also free, and constantly updated. It is widely supported by a range of scientists who are constantly contributing new packages that expand the capability of R. R will be around for the long term, so any effort you invest in learning the software will be useful throughout your career. As there are so many avid users around the world there are many online help sites and discussion boards with free code and advice.

See [http://www.r-project.org/ http://www.r-project.org/] for further details. 

Read the [[Media:R-intro.pdf|first chapter of the R-intro.pdf document]] to further expand your knowledge (6 pages). 

In summary, if you want to do serious statistics, then you need a professional statistics package, not Excel. There are a number of software packages available (e.g. SAS, Stata and R), but R is one of the best and it is free. It is a little harder to use than Excel because you have to learn some scripting commands, but it is well worth the effort. We will start by telling you what software you require. We will then lead you through Case study 1 again. You can begin to use R.

== Software to download ==
There are only two pieces of''' free''' software to download. These will give you the complete tools of a statistician! These are R and RStudio. Some of you may need to get your IT people to assist you to do this as you may not have the necessary permissions on your computers.

===R===

Please download R from a CRAN mirror, preferably either:


{| style="border-spacing:0;"
| style="border:none;padding:0.026cm;"| [http://cran.repo.bppt.go.id/ http://cran.repo.bppt.go.id/] 
| style="border:none;padding:0.026cm;"| Agency for The Application and Assessment of Technology 

|-
| style="border:none;padding:0.026cm;"| [http://cran.unej.ac.id http://cran.unej.ac.id] 
| style="border:none;padding:0.026cm;"| The University of Jember 

|}
Most of you will download the R for windows version, and this would be preferred unless you have a MAC. Once downloaded, run the file and install the program. 

===RStudio===

RStudio is a development environment for R. One of the most useful features of RStudio is that you can create files of R code that you can store, archive and send easily to R for implementation. It makes writing and running R code easier. Essentially RStudio allows you to create an R code file, work on it with text editing capability and send it to R for running.

See http://www.rstudio.com/ide/ for further details. 

Please download RStudio from http://www.rstudio.com/ide/download/.

== Exercise ==
# Open R studio 
# [http://youtu.be/MaxT90ao0jQ '''Watch the video - Introduction to R''']
# Repeat Case study 1 from this Data Analysis course, but in R (using R studio) instead of Excel.

== Further development of R and statistical skills ==
Purchase an R introductory statistics book, read it and do the exercises. ''Introductory statistics with R ''by Peter Dalgaard (Dalgaard, 2008) is excellent ([http://www.springer.com/statistics/computational+statistics/book/978-0-387-79053-4 http://www.springer.com/statistics/computational+statistics/book/978-0-387-79053-4]). 

Complete reading [[Media:R-intro.pdf|"An introduction to R"]] 

Browse the website Quick-R ([http://www.statmethods.net/ http://www.statmethods.net/])

Practice and don't give up! You will improve and it will be worth the effort.