Visual Support of Bayesian Reasoning

The process of using data visualization to explore hypotheses and build knowledge is common in visual analytics and data science. Bayesian methods formalise the relationship between prior and new knowledge in the light of evidence. Yet despite the apparent compatibility of the two approaches,  Bayesian approaches are not well supported in most data visualization / visual analytics environments. This PhD topic would explore new visual analytic designs and approaches to support Bayesian Reasoning.

Objectives (can focus on a subset of these)
 - Review Bayesian approaches in visualization and data science
 - Develop new methods of Bayesian data visualization
 - Evaluate use of visual Bayesian reasoning in a data science context
Skills/interests - Visual data science
 - Statistical methods (including Bayesian approaches)
 - Statistical graphics
 - Visualization / statistical graphics programming (e.g. R, Python, D3)

This topic was suggested by Professor Jo Wood. Please direct further enquiries to the giCentre.