Cluster analysis in R with Cait Robinson

This talk and workshop will introduce you to k-means cluster analysis using RStudio. K-means clustering groups similar items in the form of clusters. It is a useful approach for identifying patterns in a multi-dimensional dataset. During the session we will run through the fundamentals of the technique in an accessible way. We will also consider how best to visualise the outputs of our clustering. The session will focus on the example of energy inequalities in Greater London, but the technique has a wide range of application areas across different disciplines and sectors. After an introduction to the technique, you will have time to have a go of the clustering yourself. All of the code, and detailed walk throughs, will be provided.

**Please bring a laptop so you can fully participate in the workshop.**

After the workshop, we will have ample time for networking and chat over some snacks and drinks (courtesy of the Software Sustainability Institute).

Cait is a quantitative human geographer, her research investigates the causes and consequences of different types of spatial inequality, with a particular interest in energy, climate and urban inequalites. She uses spatial, quantitative datasets and methods to understand inequality across multiple scales.
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In 2022 she joined the University of Bristol as an Academic Fellow and Proleptic Lecturer in the School of Geographical Sciences. She is currently a UKRI Future Leaders Fellow, working on a four year project mapping ambient vulnerabilities in cities.