The power of R scripting – don't be afraid of code

R is not for me, right?

I always thought R was for statistics nerds only, not to be used for analyses in “normal” UX research. But then I was forced to use it in a recent project and its power and elegance impressed me. How did I end up using R? We created a dashboard for one of our clients with various UX KPI across a range of products. The dashboard was created in Microsoft PowerBI, which provides great data visualization tools and allows the user to create custom analyses with a few clicks. But it does not do statistics well, relying on R integration instead.

Why R? Some examples

A couple of examples that make R such a pleasure to use:

• Typical procedures are super simple: calculating a KPI from multiple columns per participant is a one-liner because R treats data as vectors new_value <- rowMeans(…)
• Running different statistical tests depending on the data’s properties (e.g. sample size, distribution) is very easy: write your own function if (data property = X) return (statistical test Y) and use it throughout your code.
• Working with larger data sets is very convenient, because you can use subsets of data on the fly with the “subset” function.
• Data transformation is quick and powerful: Convert data from long to wide, differentiating separate measurements, with a function called “dcast”.

All of this is also possible in SPSS, but it would require a lot of clicking through dialogues and assistants. For somebody like me who isn’t much of a SPSS syntax pro, I was surprised how easy it was in R.

The power of the community

But of course, learning R meant a lot of questions – it’s not something you learn in an afternoon. However, R has such a large and helpful community that there’s almost always an answer out there. There are numerous pages that tell you about the basics of using R, and whenever I had a more specific problem, I would almost always find the solution in one of the many active online communities. Learning R might be a bit difficult, but you’re definitely not alone.

Packages for every occasion

The solutions you find online will often use so-called packages through which you can expand R’s features. And R being open source means there are packages for almost any occasion, created and verified by the community.

"My suggestion: Get RStudio, get real data to work with, check out the tutorial pages and: have some patience!"

R in a nutshell

R is a programming language that is free to use under the GNU licence. It comes with a broad set of statistical functions and can be expanded almost infinitely with the help of packages provided by the community. Development environments such as RStudio make life a lot easier.

My suggestion: Get RStudio, get real data to work with (to prevent playing around aimlessly), check out the tutorial pages and: have some patience!

Here you can find RStudio and tutorials:

• R project
• R studio
• R tutorials
• R basic statistics

Is R for me?

Final words

I probably wouldn’t have started using R had I not been “forced” to by PowerBI. But in retrospect, I’m glad I did! If you own SPSS, you won’t be using R for a quick mean or statistical test. However, if you know you’re going to be doing more extensive data transpositions and analyses, and potentially do them repeatedly, R might be worth looking into. Especially if SPSS seems to make what you are trying to do unnecessarily complex. I will definitely use R for future projects.