e-Learning Resources

Stats4SD produce a number of e-Learning resources. These include the Statistics in Applied Climatology (SIAC) training courses, which give people working with climatic data the skills they need to use historical datasets effectively; and Statistics Made Simple (eSMS). We developed these when we were at the Statistical Services Centre of the University of Reading (SSC) in response to a growing need for statistics training that focuses on the practical application of statistics.

Video Tutorials

Over the years, together with our colleagues SSC, we generated over a hundred video tutorials covering such topics as Experiments with Farmers, R, ODK, Data Entry and Organisation, Data Flow, CS-Pro, Data Management Support, IT Productivity Tools and Dataverse Videos. These are currently held on the SSC YouTube channel.


Stats4SD is working towards helping our partners and clients in developing and using apps for their research and development work.

Highlighed here is the “Data Loops Demo” which was built to demonstrate the an example closing the data-information loop. The app collects data using an inbuilt ODK form, sends it to a non-SQL server which in turn is interrogated by an R server that processes the data. The app retrieves in real time the output for the user to see the results.

Our apps are downloadable on our Google Play account. Others include the Sorghum Variety Catalogue and Portal de Quinua. Our code for several projects can be found at our GitHub page.

Other Training Materials

Other training materials include the SADC: Course in Statistics, a complete training pack based on the South African Development Community (SADC) harmonised syllabus. This can be found through this link on the website of the Statistical Services Centre, University of Reading.

Statistics and Data Management Guides

Guides created at the Statistical Services Centre at the University of Reading can be found below. These cover several topics on Statistics and Data Management, including Planning a Research Project, Data Collection, Data Entry and Organisation, Statistical Analysis, Interpretation and Write-Up and Using Participatory Methods in Research.

Statistical Packages

We developed Instat, a general statistical package, whilst at the Statistical Services Centre, University of Reading. It is simple enough to be useful in teaching statistical ideas, yet has the power to assist with research in any discipline that requires data analysis. We are currently in the process of developing R-Instat, a beta version of our new open source statistics software. Through generous contributions via our Chuffed page, we gathered a core team to create the new software. R-Instat has been tested in workshops with the AIMs students in Tanzania, and the first release will be in July 2017.