R is a software language for carrying out both complicated and simple statistical analyses. Data summary and exploration, graphical presentation and data modelling are routines that can be carried out in R. It is a programming language which consists of a large library of pre-deﬁned functions that can be used to perform statistical data analysis. It requires some knowledge of R programming to use it well.
R is an open source software which means it is not produced and sold by commercial organisations but is collaboratively written by teams of volunteers. Being open source, it is distributed for free so anyone can modify and distribute it themselves provided the requirements of the open source licence is met.
R is downloadable from http://cran.r-project.org/. It works interactively – type a command and press enter then R executes this command, often the result would be printed; R then waits for more input and type q () to quit R.
My goal is to document aspects of R programming I’ve used in performing statistical analysis in form of tutorials hoping that you will find it useful as a statistics toolbox. Personally, I found it easier to learn R by using familiar data I had previously analysed using other software like SPSS. Though R has a wide range of documentation, I discovered most tutorials tend to start with the commands, objects and functions. Therefore, rather than start with the basic commands, objects and functions, I would in the next tutorial demonstrate how to get your data into R.
Categories: R programming