R & QGIS: Integrating Statistical and Spatial Data Analysis

This intermediate workshop consists of three sessions with a focus on developing skills in data visualisation, analysis and integration using both R studio and QGIS. Each session in the workshop begins with 40-minute presentation of the principles to be covered, before a practical exercise is offered. The exercises facilitate first-hand experience with exactly how these skills can be put to use in a practical manner.  

Friday 30 April: The first session offers an introduction to more advanced analysis and visualisation of datasets in R. The presentation shows how different aspects of datasets can be picked out, analysed and compared to one another, rather than simply using R to produce graphs of the dataset itself. The practical exercise focusses on an example of urban data, showing how the rank size rule can be used to understand trends in the different populations of cities. This use of real data in a specific example showcases the possibility for more advanced analysis of statistical data in R. 

Friday 7 May: The second session acts to show how QGIS can be used to deepen understanding of the urban data analysed in session one. The presentation focuses primarily on emphasising how analysing the same data with different software, one statistical the other GIS, can produce very different results, without changing the data themselves. The practical exercise continues with the urban example from session one, but focusses on the physical location of the cities, the spatial data. This shows how closely modern roads connecting the cities line up with least cost path analyses as well as visualising the relationship between the physical location and population size of the cities.  

Friday 14 May: The final session builds on the first two in order to show how R and QGIS can be effectively integrated. The presentation demonstrates how QGIS can be used to generate additional data and how these data can then be analysed in R. In the practical exercise, the urban example is again used. This applies demographic data to the cities, and allows for new values to be added to the dataset of cities based on raster values surrounding the cities. These new values are then imported into R and analysed and visualised in new ways.   

This workshop aims for participants to develop a deeper understanding of both R and QGIS. Crucially, this emphasises how the two can be integrated in order to understand and visualise any statistical and spatial data in a manner not possible when relying on only one of the two. 


Due to high demand for our training events, our cancellation and no-show policy applies to bookings for this event. Click here for details of this policy.