Australian National University, 2001. β 112 p.
R implements a dialect of the S language that was developed at AT&T Bell Laboratories by Rick Becker, John Chambers and Allan Wilks. Versions of R are available, at no cost, for 32-bit versions of Microsoft Windows for Linux, for Unix and for Macintosh systems 8.6 or later. It is available through the Comprehensive R Archive Network (CRAN). Web addresses are given below.
The citation for John Chambersβ 1998 Association for Computing Machinery Software award stated that S has forever altered how people analyze, visualize and manipulate data. The R project enlarges on the ideas and insights that generated the S language.
Here are points relating to the use of R that potential users might consider:
R has extensive and powerful graphics abilities, that are tightly linked with its analytic abilities.
Although there is no official support for R, its informal support network, accessible from the r-help mailing list, can be highly effective.
Simple calculations and analyses can be handled straightforwardly, albeit (in the current version) using a command line interface. Chapters 1 and 2 are intended to give the flavour of what is possible without getting deeply into the R language. If simple methods prove inadequate, there can be recourse to the huge range of more advanced abilities that R offers. Adaptation of available abilities allows even greater flexibility.
The R community is widely drawn, from application area specialists as well as statistical specialists. It is a community that is sensitive to the potential for misuse of statistical techniques and suspicious of what might appear to be mindless use. Expect scepticism of the use of models that are not susceptible to some minimal form of data-based validation.
Because R is free, users have no right to expect attention, on the r-help list or elsewhere, to queries. Be grateful for whatever help is given.
There is no substitute for experience and expert knowledge, even when the statistical analysis task may seem straightforward. Neither R nor any other statistical system will give the statistical expertise that is needed to use sophisticated abilities, or to know when naΓ―ve methods are not enough. Experience with the use of R is however, more than with most systems, likely to be an educational experience.
While R is as reliable as any statistical software that is available, and exposed to higher standards of scrutiny than most other systems, there are traps that call for special care. Many of the model fitting routines in R are leading edge. There may be a limited tradition of experience of the limitations and potential pitfalls of some of the newer abilities. Whatever the statistical system, and especially when there is some element of complication, check each step with care.