Statistics for Sustainable Development > Blog > Statistical modelling with R: Training Tips on how to keep Participants Engaged

Case Studies

Statistical modelling with R: Training Tips on how to keep Participants Engaged

Since 2014, I have been providing Research Methods Support to McKnight Foundation funded projects in Eastern Africa. Currently, I am based in Uganda and sit within Makerere University (Kampala), where 40% of my time is allocated to work with students within the University. Last summer, I was requested to take on an additional task that involved taking PhD students (Agriculture and Rural Innovations) through practical sessions on statistical modelling with R. This struck me as both an exciting and challenging task, and I set to work by discussing with my supervisor and colleagues on how best to approach the training.

The view from outside Makerere University, Kampala in Uganda

Since my requests for a data set to use during the session did not yield any results, I decided to use some of the experimental data sets from Stats4SD that are used for introducing project teams to R. During the first training session, it was clear that the students (or the course they were undertaking) were mostly prepared for using survey study designs, and that most of the experimental jargon was new to them. By the end of this initial session, it was clear that working with experimental data was not the way to go and I needed to change strategy. The next option was to request a data set from the students that they could all relate to. Unfortunately, the students had not yet collected any data and we could therefore not pursue this option. So finally, I went for the third option that involved using an old US Employee data set. With this, the students could easily relate to what they had covered in the theoretical part of the class - and were able to actively participate.

During the week of training, the following topics were covered: