It’s a reasonable question given R’s reputation as a tool for the extremely quantitatively inclined. But R can do a ton for you even if your statistical analysis needs are simple. I only ever use R for descriptive stats, and I get a ton of value from it.
People new to R often don’t realize everything that it makes possible on top of data anlaysis. In particular, RMarkdown makes reproducibility the norm so that you can create a report in seconds (something I did in a recent Demystifying R webinar), easily update a report you wrote last year with this year’s data (see below), or create several hundred reports with one line of code.
I was particularly excited, then, by the most recent My R Journey interview I conducted. Sharla Gelfand is a statistician, but, as she puts it, “the most statistical thing I do these days is calculate a median.” I was surprised to hear this (as a non-statistician, I assume statisticians spend most of their time on complicated analyses), but it reinforced what I’ve been thinking recently: R is a workflow tool first and foremost.
Sharla gives a great example in her interview of how she and her team at the College of Nurses of Ontario transitioned a report that had been done in SPSS and Excel in previous years to R this year. The extra time they spent this year on this transition will make future years take a fraction of the time.
All of this has gotten me thinking about what R truly is. Of course it’s many things to many people, but at its core, I think R is about improving your workflow. No matter if you’re doing complex statistical analysis or you’re producing tables of descriptive stats, R can help you produce and share your results more efficiently than any other tool. And that is something everyone can benefit from.