Each questions have to be; coherent and cohesive, a minimum of 200 words and you have to cite one sources. This is a Project Risk Management Course
· 1. Name six likelihood drivers and three consequence drivers in technical projects involving a mix of hardware and software.
· 2. Demonstrate two approaches to the conversion of descriptive likelihood assessments to numerical priority measures (using for risk likelihood and for average consequence) and explain the characteristics of each.
· 1. Define the term ‘aggregate uncertainty’ in the context of using quantitative risk models.
· 2. What are some of the uses for quantitative models when analysing a project?
· 3. Name three categories of information that we could derive from the outputs from quantitative risk models. How could they assist a decision maker (such as the project director)?
· 4. Describe five contextual features that should be addressed when using a risk modelling approach.
· 5. Discuss why the structure of a quantitative risk model may differ from a simple spreadsheet for a capital cost estimate.
· 6. Why is model validation important?