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# Part 80: Representations of Uncertainty

//Part 80: Representations of Uncertainty
Part 80: Representations of Uncertainty2022-08-21T03:58:04+00:00

Part 80: Representations of Uncertainty
(Project Risk Management: Perform Quantitative Risk Analysis)

• We don’t always know what the exact duration or cost of an activity will be, but we might have a range (a set of values)
• Each value in the range may have a different probability of occurring
• We represent the values in a probability distribution
• There are many types of distributions, including triangular, normal, uniform, and discrete
• We should select the type of distribution that best represents our data
• We might have a different distribution for each risk
• For example, the cost of installing a window will probably be \$1000, but between \$500 and \$1500.  We have a range.  The actual cost might be any value between \$500 and \$1500.  We have a 50% chance that it will cost \$1000, we have a 20% chance that it will cost \$800 or \$1200, and we have a 10% change that it will cost \$500 or \$1500.  We have other percentages for other values.  This can be represented by a distribution.
• Sometimes two or more risks are related.  We call this correlation and should include it in the model. For example, if a truck carrying toxic chemicals has a crash (Risk 1), then there is a possibility that the environment will be polluted (Risk 2)