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@RISK Modeling Tips If you have a tip or example model you’d like to share, we’d love to hear from you. Send your model to: techsupport@palisade.com. @RISK 5.0 Free Live Webcasts What’s New in @RISK 5.0 @RISK 5.0 and Six Sigma
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User Conference Series
“We were very happy to meet professionals from banking, academia, oil and gas, and other industries,” noted Palisade Latin American Sales Director Denise Castellot. “The insights gained by both the delegates and staff made this a very valuable forum for quantitative risk and decision analysis.” The San Jose conference was the fourth in a global series of User Conferences from Palisade in 2007 that commenced with an event in London in April, and included stops in Miami in October and Sydney, Australia in September. Attendance at the series in 2007 was more than double that of 2006, and events are being planned for 2008. Join us next year for what has become the industry risk and decision analysis forum! » 2008 Palisade User Conference Europe, 2223 April, 2008 More dates coming soon.
by Dr. Ching Ning Guey, Florida Power & Light, presented at the 2007 Palisade User Conference A riskinformed approach to inspect piping segments has been used in nuclear power plants since mid 1990s. In one NRC accepted methodology, @RISK is used to determine the relative importance of piping segments. Such an approach has been used successfully in maintaining the same level of safety, while reducing the burden of performing inspections. @RISK has been used in accounting for the uncertainties in two key aspects of the riskinformed inspection process, i.e., the likelihood of piping failures and the consequence of such failures. » Download the presentation and example model
Making $ense of Baseball –
Building probabilities of winning and run production are brought together in a pragmatic manner (making smart bets) by utilizing the family of Palisade products, i.e, @RISK, StatTools, and BestFit. » View now: "Making $ense of Baseball" (free webcast)
Cost Estimation a) What is the probability that the project will actually be delivered within this budget? b) How much contingency (i.e. extra budget) should be included in order for this new revised budget level to be achieved with a certain degree of confidence? This model shows how one might answer these questions through @RISK Monte Carlo simulation: It is assumed that each item's actual cost will be within a minmax range, and that Pert distributions are applicable to describe the possible costs of each item in practice. The distributions are assumed to be skewed in this case, and the parameters chosen to reflect that costs are assumed to more likely overshoot than undershoot the base case. Results are given using @RISK statistics functions as well as through standard graphs and reports. » Download the example: CostEstimation.xls NCAA Tournament » Download the example: NCAA.xls New Product Profitability » Download the example: Hippo.xls
RiskBeta RiskBeta(alpha1,alpha2) specifies a beta distribution using the shape parameters alpha1 and alpha2. These two arguments generate a Beta distribution with a minimum value of 0 and a maximum value of 1. For example, RiskBeta(1,2) specifies a beta distribution using the shape parameters 1 and 2. RiskBeta(C12,C13) specifies a beta distribution using the shape parameter alpha1 taken from cell C12 and a shape parameter alpha2 taken from cell C13. RiskBetaGeneral RiskBetaGeneral(alpha1,alpha2,minimum,maximum) specifies a beta distribution with the defined minimum and maximum using the shape parameters alpha1 and alpha2. For example, RiskBetaGeneral(1,2,0,100) specifies a beta distribution using the shape parameters 1 and 2 and a minimum value of 0 and a maximum value of 100. RiskBetaGeneralAlt For example, RiskBetaGeneralAlt("min",0,10%,1,50%,20, RiskBetaSubj RiskBetaSubj(minimum, most likely, mean, maximum) specifies a beta distribution with a minimum and maximum value as specified. The shape parameters are calculated from the defined most likely value and mean. For example, RiskBetaSubj(0,1,2,10) specifies a beta distribution with a minimum of 0, a maximum of 10, a most likely value of 1 and a mean of 2.
Climate Change What is the relation of local warm spells to global warming? A new study uses Monte Carlo simulation and looks at 126 years of realworld temperature data from the city of Philadelphia. Education Finding that financial literacy can ease social problems, new research identifies factors that determine this knowledge. Neural networks analysis is used to assess financial literacy of groups of people. Investments Deutsche Postbank uses Monte Carlo simulation to model subprime related portfolio loss Law Enforcement A new traffic surveillance system makes use of a highspeed camera and a neural network. Project Management Forecasting how long a project is going to take has been a near impossible task for companies for years. This article looks at how Monte Carlo Simulation could be used to give more accurate project duration estimates. Real Estate Finance columnist suggests Monte Carlo simulation to anticipate ups and downs in property valuations. Oil and Gas Monte Carlo simulation is used to verify the closedform solution of the Dispersive Discovery model of oil and gas prospecting. Water Resources For the South Florida, the goal is to keep the level of water balanced, the quality high, and to satisfy as many stakeholders as possible. Decision trees are used to account for many different factors. The Palisade User Forums are online discussion boards where users are invited to post questions and share ideas on their use of @RISK and other Palisade software. It’s also a great place to check for announcements regarding updates of Palisade software. Forums are organized by products. » Join or view the Palisade Forums Recent topics include:
» Correlations: One RiskIndepC to Multiple DepC Functions



