Moderator: Intaver Support
1. If you have reliable historical data about task duration or cost
2. If you established eliciting judgment procedure where you asked experts questions about the their previous experience related to similar tasks.
3. To model the 'noise' or fluctuation of duration and cost which cannot be attributed to specific events.
In all other cases we recommend defining uncertainties using global and local risks.
Our analysis shows that in most real life project the type of distribution may not very critical. However there are a number of things to consider:
1. Distribution can be bounded and unbounded. All unbounded distributions in RiskyProject (normal and lognormal) have a cut offs.
2. If you have historical data, you may use Stat::Fit to generate the most appropriate distribution.
3. If you elicit judgment about distribution, you may use discrete or custom distribution.
In your case you may try beta distribution. It is easy to use bounded distribution.
If you have empirical data for Cost, Income, and Duration, you may use Stat::Fit software to generate most appropriate statistical distribution. You cannot use Stat::Fit for start time. Stat::Fit is the third party software by Geer Mountain Software (www.geerms.com) and can be purchased separately.
Fitting a distribution
1. Click on the Fit Distribution button. The Stat::Fit software opens.
2. Enter data to the Data Table. Make sure that you are entering data in the current units for RiskyProject e.g. days
3. Click on the Auto::Fit toolbar button
4. Select a recommended distribution from the list of possible distributions. Make sure that RiskyProject supports distribution you selected. RiskyProject can use only Uniform, Normal, Lognormal, Beta, Gamma, Triangular, and Exponential distributions from Stat::Fit.
5. When you are satisfied with selected distribution, click the Export button. From the list of applications, select RiskyProject. Output should be set to Clipboard (default selection).
6. Click OK.
7. Save empirical data in Stat::Fit if you which and close Stat::Fit. RiskyProject will generate distribution and assign low and high estimates for cost, income, and duration based on empirical data.