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Precise Versus Bounded Probability
What does it mean to quantify epistemic uncertainty by probability? Can there be more than one way to do it? In this discussion seminar I will compare precise and bounded probability as measures for epistemic uncertainty. I look for criteria for suitable quantitative measures of epistemic uncertainty such as a coherent theory, interpretation, the ability to learn from data in different types of situations, the ability to in a transparent way integrate expert knowledge and the ability to propagate epistemic uncertainty in a model. We focus the discussion to Bayesian inference (for precise probability) and Robust Bayesian inference (for bounded probability) and Confidence theory (for confidence boxes).
Professor Ullrika Sahlin is an Associate Professor in Environmental Science at Lund University, Sweden. She is doing research on the use of methods to treat uncertainty in scientific assessments with applications on environmental assessments and evidence-based decision making. Ullrika is leading the research group Uncertainty and Evidence Lab at Lund University.