An Introduction to Visualisation and Modelling of Spatial data (in R)

Spatial data are common in many fields like environmental monitoring and public health, however communicating spatial data is difficult. In this course your will learn how statistics is used to model, interpret and visualise spatial data.

Course leader

Dr. Eilidh Jack
School of Mathematics and Statistics
University of Glasgow, UK

Dr. Marnie Low
School of Mathematics and Statistics
University of Glasgow, UK

Target group

• Master
• PhD

This course will be useful for those who work with spatial data across a variety of fields. This course will suit anyone who is looking to learn about modelling and visualising their spatial data as well as those who would like to refresh what they have learned before. No prior knowledge of spatial statistics is required.

Course aim

After this course you are able to:
• Load spatial datasets into R and produce exploratory visualisations and summaries.
• Identify spatial trends and autocorrelation.
• Distinguish between areal unit and geostatistical data and apply corresponding methodology appropriately.
• Interpret R output and produce high quality visualisations of results.

Fee info

EUR 600: The fee includes the registration fees, course materials, access to library and IT facilities, coffee/tea, lunch, and a number of social activities.

Scholarships

We offer several reduced fees:
€ 540 early bird discount- deadline 1 April 2022 (10%)
€ 510 partner + RU discount (15%)
€ 450 early bird + partner + RU discount (25%)