My introduction to the R software was as an under graduate student of statistics. One of the teachers was very enthusiastic about it. However, at least initially, I did not share his enthusiasm for R. We were still learning the very basics of statistics and as a consequence, used R for pretty basic computations and graphs. That failed to sustain my attention.
However, things changed when I started exploring R on my own, especially in the university when I was enrolled in a post graduate course in statistics. As my knowledge and understanding of statistics increased and improved, my admiration for R followed quickly. I was taken in by the amazing data acrobatics offered, the latest theories incorporated, the open community model and last but not the least, the zero license fees!
The affair continued in my second job which is at a CRO. Though SAS is the software of choice for statistical analysis in the Pharma industry, R can work well as a validating program. I started using R to validate SAS outputs and found it very reliable and flexible. It used to take us almost a two page SAS code to compute pseudo SD, but with R, I could do that (and more!) in about five lines of code. I also developed a macro (or a set of functions to be more precise with R) which automates a regular task of validating routine SAS outputs for safety memos. Currently, as a part of the QA team, I am using R to create validators for the innovative software products developed in the company. R is not only a good choice but also the only choice when it comes to validating first to market products.
I can go on and on with R. It was R 1.4.1 when we first met, now its 2.13.0. I have seven versions of R installed on my machine at work. I wish all the best to the R team and say a heartfelt thank you. Looking forward to learning more of R and more of statistics.
