Finessing Monte Carlo Simulation Input Distribution Selection with @RISK

Presented by

Steve Van Drew

About this talk

For many spreadsheet-based Monte Carlo simulation modelers, making input distribution selection decisions can be both time consuming and angst inducing. Whether basing these decisions on goodness of fit tests when fortunate enough to have relevant data, or on insight gained from a carefully chosen expert’s judgment, the modeler often feels compelled to choose a seemingly unsuitable distribution. Fortunately for @RISK users several lesser-known features exist that allow the modeler to “finesse” their selection.

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Palisade Company is the world’s leading provider of risk and decision analysis software solutions for science and industry. Our array of software products and custom services enhance the management experience by combining the latest in cutting-edge technology with over 35 years of analytics experience. Palisade’s unified software platform helps clients increase margins, improve performance, expand market share, and maximize operational efficiencies. We have a very simple mission: to minimize risk while maximizing potential.