Researchers in computer science have found that the use of a particular programming language can have an effect on users' thinking, as well as their programming 'accent' in other languages. In statistics education, studies of graphical user interfaces like TinkerPlots and Fathom have shown statistical software can affect learners' conceptions of central tendency and variability. However, there has been limited research bringing these two areas of research together. This talk presents a case study comparing three common domain-specific languages within R: the base R syntax, the 'formula' syntax, and the 'tidyverse' syntax. The approaches are compared in terms of efficiency (primarily in the context of human programming hours, rather than runtime), efficacy, and learning outcomes.