R (and SAS)

We have many years of experience using SAS, and other proprietary closed-source software. We can work using this software, but our passion is for open-source alternatives. Where possible, Insight Statistics uses cutting-edge "R" statistical software. R is an implementation of the award winning "S" statistical programming language developed by John Chambers at Bell Labs. R started out as a "reduced" version of S, but has since grown to be much larger than its predecessor.  R has dramatically shaped the landscape of data science since its first release in 1995, and is often referred to as the ''lingua franca'' or “common language” of data analysis.


R consists of a base system plus several thousand add-on packages.  The most important packages come bundled with R and others can easily be added.  The base system is maintained by an R-Core group consisting of several distinguished statisticians from around the world.  Add-on packages are user contributed.  Statisticians often produce an R package to accompany the publication of new statistical ideas and this is what makes R software cutting-edge.  New statistical capabilities often appear in R long before they are available in other software. R also provides powerful tools for communicating results.  This includes outstanding graphical capabilities and excellent tools for producing high-quality reports.



Insight Statistics also uses RStudio software.  RStudio is an Integrated Development Environment (IDE) that makes it easier to work in R. RStudio was first introduced in 2011. It has since become the standard IDE for R.


RStudio makes it easier to write, revise, organize, and document R code across multiple projects.  It also facilitates the creation of beautifully typeset statistical reports.  Thorough its integration with R packages like "knitr," RStudio is able to automatically populate statistical reports with the results of your research.  This allows you to generate reports more quickly and efficiently.  It also puts your work on stronger scientific footing by seamlessly integrating all aspects of the research process.  For companies interested in developing their own internal capabilities, RStudio also offers excellent tools for developing R packages.