Elena Belogolovsky writes:

Congratulations to the R Core Team on receiving the 2026 Rousseeuw Prize for Statistics.

R has made creative, open-ended statistical analysis and graphics accessible to generations of statisticians and applied researchers. It has also been central to statistical research, methodology, and applications during decades when statistics became more computational and more important across science, engineering, business, and public health.

One of the great strengths of R is that it is not just a software platform. It is also a community. The system of R packages allows anyone to implement a new method and share it with the world, helping make statistical research more open, useful, and alive. R has also been the medium for major developments in statistical graphics, transforming applied statistics and the way people work with data.

The volunteers who have developed, guided, and maintained R and the R community are richly deserving of this major award.

I agree with the committee that the R team is an excellent recipient of this award. I say this for several reasons:

– Most obviously, R is super-useful and it’s changed statistics, both by enabling more complicated and reliable analysis and by establishing a common language for statistical coding.

– R integrates statistical modeling with graphics, which traditionally (but, in my opinion, mistakenly) have been thought of as in opposition.

– R is open source. This might sound like no big deal, but its predecessor was Splus, which was a commercial package. Before that came S, which was open but was not set up to expand in a scalable way.

– With its system of packages, R became modular: different groups of users (including me!) could write their own packages and develop new and useful tools without needing to get tangled in core R issues. For example, we have cmdstanr, which lets you run Stan programs from R. This is super-useful for Bayesian workflow.

– R is a programming language, not a menu-based set of commands. This is no big deal now, given that the natural comparison to R is Python, but, back in the day, when R’s competitors were Sas, Spss, Stata, etc., it was a big deal that with R you write programs, you don’t just push buttons. A big deal for workflow in statistics and data science.

– Regarding the R community . . . ok, this gets complicated. Still and all, the R core team is very helpful to outsiders and has been a clear net benefit to the communities of developers, statisticians, and users.

I’m sure I’m missing a few things. My only disagreement with the award citation is that it doesn’t mention S, the statistical software environment developed by John Chambers and others at Bell Labs back in the 1980s. R is a rewrite of S. With lots of improvements, but I do think the S team deserves credit for setting up the template.