Guidance for teaching R programming to non-statisticians
David D. Langan, Anne Wade · UCL Discovery (University College London) · 2016
The Centre for Applied Statistics Courses (CASC) at University College London (UCL) provide short courses on statistics and statistical software packages. Popular day-courses include a wellestablished ‘Introduction to R’ course and the newly developed ‘Further Topics in R’. In the latter, attendees are taught intermediate-level topics such as loops and conditional statements. Attendees range from postgraduate students, academic researchers and data analysts in the private sector without a strong background in statistics or programming. First, we highlight some issues with providing our training course to this demographic, derived from our experience and from anonymous online feedback. Second, we discuss some of our solutions to these issues that have shaped our course over time. For example, one issue is catering to a wide audience from differing fields, different levels of computer literacy and approaches to learning. To address this, we prepare for a high level of flexibility on the day and include intermittent practical exercises to get real time feedback on the abilities of attendees. Finally, we reviewed the experiences of other teachers on similar courses documented online and compared these experiences with our own. We offer guidance to other teachers running or developing courses for intermediate-level R programming.