Bachelor of Biotechnology Innovation (Hons) Biotechnology, Business. Queensland University of Technology.
- Statistical Uncertainty
- Data Visualisation
- Bayesian Hierarchical Models
- Science Communication
- Geospatial Health Data and Disease Mapping
Title : Using Graphs to Communication Statistical Uncertainty In Disease Maps to Decision Makers
Project Partner: CRC for Spatial Information, Cancer Council Queensland, National Health Performance Authority & QUT
Uncertainty pervades every part of our lives. Everyday we plan for the future and attempt to make the best decisions we can based on the available information that we have. Knowing the quality and certainty of the data we have can enable us to make better decisions; telling us how much weight to give to the information we have, where and when to collect more information, and how variable an event may be. This project explores how best to communicate statistical uncertainty in disease maps, of cancer incidence in Australia, to policy makers and other decision makers.
Recommended Resources for Uncertainty and Uncertainty Visualisation
- Collection of Uncertainty Visualisation Examples on Pinterest (You will need to have a Pinterest account to access. These resources will be moved shortly to a open access platform).
- Science Visualisation: Uncertainty, Multifield, Biomedical, and Scalable Visualization. Editors: Hansen, C.D., Chen, M., Johnson, C.R., Kaufman, A.E., Hagen, H. (Eds.)
- Bordoloi, U., Kao, D., Shen, H.N.: Visualization techniques for spatial probability density function data. Data Sci. J. 3, 153-162 (2005)
- De Cola, L. (2002). Spatial forecasting of disease risk and uncertainty.Cartography and Geographic Information Science, 29(4), 363-380.
- Boukhelifa, N., Duke, D.J.: Uncertainty visualization: why might it fail
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