MacResearch

Statistical analysis can be a painful and laborious facet of the MacResearcher's daily life. Commercial and all-in-one statistical software can be great, but quite often the need arises to build our own unique statistical tools. This often entails the development of a PERL script or a crazy Excel macro in which the statistical wheel is reinvented many times over. Enter the R-Project. Think of "R" (yes that's the name, this project needs a marketing department) as the swiss army knife of statistical software tools. It's a robust statistical environment with an intuitive programming language and an expansive collection of computational and graphical modules that allow rapid development of custom statistical tools. R is easily extended through a package system and it can even be linked to C, C++, and Fortran code at runtime.

R enjoys widespread development and use in the scientific community and several important software projects use R at their foundation. Here are some notables:

• BioConductor - an open source software project for the analysis and comprehension of genomic data.


• The Omega Project - distributed statistical computing.


• gR - Graphical Models in R.

R enables the most non-technical of researchers to develop custom statistical tools rapidly and relatively easily. For the hard-core techie, R provides enough power and extensibility to be considered for the most complex statistical analysis scenarios.

Information on installing and using R on Mac OS X can be found on the R for Mac OS X download page.