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EN
A quantitative risk analysis (QRA) should provide a comprehensive, informative and balanced picture of risk, in order to support decisions. To achieve this, a proper treatment of uncertainty is a prerequisite. Most approaches to treatment of uncertainty in QRA seem to be based on the thinking that uncertainty relates to the calculated probabilities and expected values. This causes difficulties when it comes to communicating what the analysis results mean, and could easily lead to weakened conclusions if large uncertainties are involved. An alternative approach is to hold uncertainty as a main component of risk, and regard probabilities as epistemic-based expressions of uncertainty. In the paper the latter view is taken, and we describe what should be the main pillars of a risk description following this approach. We also indicate how this approach should relate to decision-making. An important issue addressed is how to communicate the shortcomings and limitations of probabilities and expected values. Sensitivity analysis plays a key role in this regard. An example is included to illustrate ideas and findings.
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