Probabilistic Risk Analysis With Hardly Any Data
A tutorial workshopto be held in conjunction with the
Society for Risk Analysis Annual Meeting
8:00 - 5:00 pmSunday, 6 December 2009
Renaissance Inner Harbor Hotel
Baltimore, Maryland
This tutorial explains how you can develop a fully probabilistic risk analysis even though there may be very little empirical data available on which to base the analysis. It compares the strengths and weakness of various approaches.
Synopsis Overview of topics Presenters Registration Venue in Baltimore More information Related links
This full-day tutorial introduces and compares methods for developing a probabilistic risk analysis when little or no empirical data are available to inform the risk model. The talks are organized around the basic problems that risk analysts face: not knowing the input distributions, not knowing their correlations, not being sure about the model itself, or even which variables should be considered. Possible strategies include traditional approximative methods and recent robust and bounding methods. Numerical examples are given that illustrate the use of various methods including traditional moment propagation, PERT, maximum entropy, uniformity principle, probability bounds analysis, Bayesian model averaging and the old work horse, sensitivity analysis.
All of the approaches can be used to develop a fully probabilistic estimate useful for screening decisions and other planning. The advantages and drawbacks of the various approaches are examined. The discussion addresses how defensible decisions can be made even when little information is available, and when one should break down and collect more empirical data and, in that case, what data to collect. When properly formulated, a probabilistic risk analysis reveals what can be inferred from available information and characterizes the reliability of those inferences. In cases, where the available information is insufficient to reach dispositive conclusions, bounding probabilistic risk analysis provides a compelling argument for further empirical research and data collection.
The presentation style of the tutorial will be casual and interactive. Participants will receive a booklet of the illustrations and numerical examples used during the tutorial and a CD with these files for their personal use.
Scott Ferson is a senior scientist at Applied Biomathematics where his research focuses on developing reliable mathematical and statistical tools for risk assessments and on methods for uncertainty analysis when empirical information is very sparse. Ferson holds a Ph.D. from the State University of New York at Stony Brook. He is author of RAMAS Risk Calc Software 4.0: Risk Assessment with Uncertain Numbers (Lewis Publishers). He has written over 100 other scholarly publications, including four other books and several software packages, in environmental risk analysis and uncertainty propagation. His research has addressed quality assurance for Monte Carlo assessments, backcalculation methods for use in remediation planning, and distribution-free methods of risk analysis appropriate for use in information-poor situations.
Jack Siegrist is a quantitative ecologist in the Ecology and Evolution Graduate Program in the Department of Ecology, Evolution and Natural Resources
at Rutgers University in New Brunswick, New Jersey. He holds degrees from University of Texas at Austin and Southeastern Louisiana University. He is also a research scientist at Applied Biomathematics
where his research focuses on risk perception, uncertainty comparisons, and combinatorial methods for detecting clusters in small data sets.
The registration fee is $240 by 6 November, or $290 on site. You do not need to register for the Annual Meeting to attend the workshop. Registration will be handled by
The workshop will be 8:00 - 5:00 on Sunday, 6 December 2009, in Baltimore's beautiful Inner Harbor neighborhood at
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Renaissance Baltimore Harborplace Hotel 202 East Pratt Street Baltimore, Maryland 21202 On-line reservations Phone: 1-410-547-1200 Fax: 1-410-539-5780 Toll-free: 1-800-535-1201 |
The meeting room for the workshop has not yet been determined; check with the hotel concierge on Sunday morning for directions to the meeting room.
Reserve a room at the hotel on or before 13 November 2009 to obtain the SRA rate of $154 per night (single/double occupancy) plus 13% tax. Be sure to mention the Society for Risk Analysis to receive the SRA group rate. This rate is available as early as 4 December, subject to availability. Remember the cut off for this rate is 13 November 2009, or until the SRA room block is sold out. The base room rate thereafter will be $199. Reserve your room early. Cancellations must be made by 6 pm hotel time on the day of arrival. You can make hotel reservations on line or by telephoning 1-410-547-1200 or (toll-free) 1-800-535-1201. Be sure to mention the SRA when making a reservation. For more information about the venue, see the hotel fact sheet, a map of the area, or driving directions.
Weather in Baltimore is likely to be cold and may be wet in early December. The average high temperature in Baltimore in early December is 55 °F (13 °C) and the average low is 38 °F (3 °C).
More information can be obtained from Scott Ferson scott@ramas.com, telephone 1-631-751-4350, fax 1-631-751–3435.
Society for Risk Analysis www.sra.org
Society for Risk Analysis Annual Meeting http://www.sra.org/events_2009_meeting.php
Hotel reservations http://www.marriott.com/hotels/travel/bwish-renaissance-baltimore-harborplace-hotel/?toDate=12/10/09&groupCode=srasraa&fromDate=12/4/09&app=resvlink
Hotel fact sheet http://www.marriott.com/hotels/fact-sheet/travel/bwish-renaissance-baltimore-harborplace-hotel/
Baltimore Wikipedia entry http://en.wikipedia.org/wiki/Baltimore
Weather in Baltimore http://www.wunderground.com/US/MD/Baltimore.html
The Imprecise Probabilities Project http://www.sipta.org/
Sandia National Laboratories' Epistemic Uncertainty Project http://www.sandia.gov/epistemic/
Intervals and Probability Distributions website http://ifsc.ualr.edu/jdberleant/intprob/
NSF workshop on risk perception and communication http://www.ramas.com/riskcomm.htm