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MATH2010 – Statistical Methods I R Worksheet 1

What is R?

R is a language and environment for statistical computing and graphics, which is similar to the S language and environment which was developed primarily at the AT&T research laboratories during the 1980s. The most common implementation of S is through the proprietary Statistical package S-Plus (which you may encounter in MATH3012). R, on the other hand is open source, and freely available from http://cran.r-project.org/, making R code extremely portable. R and S retain much in common, and knowledge of R makes it easy to use S and S-Plus if you have access to them; code written in R will usually run in S (and vice versa) As well as having the usual facilities for statistical modelling, data handling and graphical display, in common with many other statistical packages, R also allows the user great flexibility in manipulating and analysing data. It is also highly extensible, allowing users to develop bespoke methods for data analysis, and has become the computational tool of choice for many Statisticians working in research and development. R is object-oriented, which means that everything is stored as a particular type of object, with different operations being appropriate for different types of object. For example, vectors and matrices are both types of object in R. Data are usually stored in a data frame object, and results of statistical analyses are stored in an object of the appropriate type, for example when you fit a linear model, the results are stored as a linear model object. In R, most operations are performed by executing functions; see below for more details;

Course Data

A number of data files, some of which we shall use during the course, are stored on the University central file server. To make these files available on the R: drive of your computer, follow the path All Programs → Course Folders → Access to Course Folders. The R: drive is opened and the course folders are immediately visible. You...