PMI-RMP Certification Training - Latin Hypercube Stratified Sampling

The video tutorial explains the differences between Monte Carlo and Latin Hypercube methods, highlighting how Latin Hypercube achieves similar results with fewer iterations by using intervals. It then outlines guidelines for conducting quantitative risk analysis, including reviewing management plans, using historical data, and performing sensitivity analysis. The tutorial concludes with instructions on updating risk analysis reports and project documents, emphasizing the importance of tracking project risks and responses.

What is the primary difference between Monte Carlo analysis and Latin hypercube sampling?

How does Latin hypercube sampling ensure that the output of the simulation is equally spread out?

What steps should be taken to perform quantitative risk analysis according to the text?

What role does historical information play in the risk analysis process?

What is the significance of conducting a sensitivity analysis in risk management?

How can trends in quantitative risk analysis results inform planning for risk responses?

What should be included in the risk report according to the text?