The Probability of completing a project within a given time frame depends on various factors such as project complexity, resources, team expertise, potential risks, and uncertainties.
To estimate the probability of completing a project within a specified time, you would typically use project management techniques such as Critical Path Analysis (CPA), Monte Carlo simulation, or PERT (Program Evaluation and Review Technique). These methods help in analyzing the project schedule, identifying critical tasks, estimating task durations, considering dependencies, and accounting for uncertainties.
Once you have these inputs, you can run simulations to generate a probability distribution of project completion times. This distribution can then be used to calculate the probability of completing the project within the desired time frame.
An advantage of using probabilistic time estimates is the ability to predict the probability of project completion dates. We learned how to calculate the expected time for each activity with the three time estimates provided. Now we need to calculate the variance for each activity.
The variance of the beta probability distribution for each activity is:
Where
p = pessimistic activity time estimate
o = Optimistic activity time estimate
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