Introduction to Quantitative Risk Analysis


This course will cover the most important principles, techniques and tools in Quantitative Risk Analysis. The focus of the course is on how to conduct accurate and effective risk analyses, including framing a risk analysis problem, best practices of risk modeling, selecting the appropriate probability distribution, using data and expert opinion, and presenting risk analysis results. In addition, the course will cover an introduction to probability and statistics theory and various stochastic processes, which is critically important to a solid understanding of quantitative risk analysis.

The course will also familiarize participants with risk analysis modeling environments in Excel (course participants can use @RISK from Palisade, Crystal Ball from Oracle, or ModelRisk from Vose Software), but the lessons and techniques apply equally well to other modeling environments). The course will also cover common mistakes made when doing quantitative risk analysis and how to avoid them.

Please note this is a four week course ending on 10th May 2013.

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Published features on are checked for statistical accuracy by a panel from the European Network for Business and Industrial Statistics (ENBIS)   to whom Wiley and express their gratitude. This panel are: Ron Kenett, David Steinberg, Shirley Coleman, Irena Ograjenšek, Fabrizio Ruggeri, Rainer Göb, Philippe Castagliola, Xavier Tort-Martorell, Bart De Ketelaere, Antonio Pievatolo, Martina Vandebroek, Lance Mitchell, Gilbert Saporta, Helmut Waldl and Stelios Psarakis.