CEEM594 - Risk Attitudes and Key Assumptions in Utility Theory

Course Description

Making a decision often isn't as simple as choosing between Choice 1 and Choice 2 because one option is clearly better than the other. In the real world, not only are there complexities regarding financial costs, but there are deeper considerations around risk. Adding risk into the equation then requires considering whether the more profitable option is not worth the risk, and adding utility theory allows for the proper modeling of these complex choices. Risk and other considerations can subsequently be placed into a decision tree for further evaluation.

You have explored how subjective probabilities and the value of information can be integrated into your decision analysis. In this course, you will examine how risk attitudes and utility theory also impact your decision analysis. You will identify how risk attitudes are related to several axioms and paradoxes. You will also use utility theory to devise a model for quantifying subjective inputs to a decision then apply these additional considerations to a decision tree framework.

Risk and utility theories have the potential to totally change how you may have originally framed your decision, but this fuller picture provides invaluable insight into how you should make your decisions. It will also offer clearer context for when you incorporate more complicated analysis tools into your analysis process.

Faculty Author

Benefits to the Learner

• Be a critical consumer of how risk attitudes are elicited and computed then incorporate them into decision analysis
• Link the use of risk attitudes to utility axioms and paradoxes to frame decisions
• Use utility theory to devise a model for quantifying subjective inputs to a decision
• Balance conflicting fundamental objectives and additive utility for evaluation problems to quantifying subjective inputs to a decision
• Balance conflicting objectives within multi-attribute utility models with interactions to apply these additional considerations to a decision tree framework

Target Audience

• Engineers in any field, including mechanical, electrical, civil, and environmental
• Aspiring data scientists, data analysts, and market analysts
• Anyone who needs to make highly consequential decisions or inform solutions in the face of uncertainty or multiple and conflicting objectives

Applies Towards the Following Certificates

• Decision Analysis : Core Courses