QBUS3330: Methods of Decision Analysis

University of Sydney• 2025 S2
In Progress
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RiskAssessment
DecisionTrees
ManagerialDecisionMaking

Provides formal methods for decision-making under uncertainty using probabilities, decision trees, sensitivity analysis, and simulations to evaluate choices and improve managerial decision quality.

Learning Outcomes

  • Scope recognition: Identify which problem types decision analysis can and cannot address.
  • Problem structuring: Elicit and organise values, objectives, attributes, decisions, uncertainties, consequences, and trade-offs for a real decision problem.
  • Decision quality concepts: Apply expected value, value of information, risk aversion (utility), and multi-attribute trade-offs to identify good decisions and strategies.
  • Modelling & representation: Represent decision problems graphically and/or mathematically (e.g., decision trees, influence diagrams).
  • Optimization of choices: Determine optimal decisions via expected value/expected utility calculations and roll-back procedures.
  • Sensitivity & drivers: Pinpoint which parameters most affect results and conduct sensitivity/what-if analyses.
  • Managerial communication: Explain results clearly to managers and other non-specialists using appropriate statistical/decision-analysis reporting.

Takeaways

Coming soon.