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Uncertainty and Risk Analysis using @Risk

Many business decisions are based on deterministic figures that have been calculated from an analysis of some kind. Because point estimates are very dangerous, to fully understand the results we need an estimate of the uncertainty related to those figures.

The learning objectives of this training session are to understand how to use the Monte Carlo simulation to carry out uncertainty and risk analysis modeling projects.

With this knowledge students will:

  • Have a better picture of the project's risk and rewards
  • Identify those variables that have the greatest effect on the outcome
  • Measure the effects of different scenarios
  • Determine the likelihood of the worst scenarios
  • Increase the probability of making better decisions

Any analysis encompasses four steps:

  1. Developing a model by defining the problem and building a model in an Excel worksheet format.
  2. Identifying uncertainty in variables in your Excel worksheet and specifying their possible values with probability distributions, and identifying the uncertain worksheet results you want analyzed.
  3. Analyzing the model with simulation to determine the range and probabilities of all possible outcomes for the results of your worksheet.
  4. Making a decision based on the results provided and personal preferences.

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Kogod School of Business FSIT Lab Training

Register for one of the training classes through the online registration form.

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