March 27
Statistical Engineering Division
Bayesian Environmental Policy Decisions: Two Case Studies

Lara J. Wolfson
University of Waterloo

Statistical decision theory can be a valuable tool for policy-making decisions. In particular, environmental problems often benefit from the application of Bayesian and decision-theoretic techniques which address the uncertain nature of problems in the environmental and ecological sciences. In this talk, I discuss aspects of implementing statistical decision-making tools in situations where uncertainty is present, looking at issues such as elicitation of prior distributions, covariate allocation, formulation of loss functions, and minimization of expected losses subject to co-operation constraints. These ideas are illustrated through two case studies in environmental remediation. One case study has incomplete data, whereas the other case study is an a priori analysis prior to the collection of data.

Date created: 6/5/2001
Last updated: 6/21/2001
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