Statistical computing tools are often separated into one of either: professional or educational tools. R is clearly a professional tool yet much of the variety of its functionality stems from the education and research industry. For decades R has remained a category leader in its provision of a functional, data as a first-class-object programming environment. Additionally R maintains its flexibility through the CRAN repository of extensions for newly required features or updates to methods which prevents users from "experiencing out" and off of the platform. What other factors are there to consider which make R a great statistical computing environment? Amelia McNamara (St. Thomas) has been studying and researching statistical computing tools for several years and has recently developed a framework of attributes which she proposes are necessary in combination to support the adoption and usability of any statistical tool. This talk is intended to be applicable for anyone interested in software design, software evaluation, data analysis and/or reproducibility.