Spring 2023 - REM 325 D100

Uncertainty, Risk, and Decision Analysis (3)

Class Number: 2758

Delivery Method: In Person


  • Course Times + Location:

    Jan 4 – Apr 11, 2023: Wed, Fri, 9:30–10:20 a.m.

  • Prerequisites:

    45 units. Recommended: REM 225 or STAT 201 or STAT 203 or STAT 205 or GEOG 251 or equivalent.



Provides a broad, yet practical, perspective on uncertainty and risk that can be used to improve decision-making abilities in a wide range of settings. Quantitative decision analysis provides a formal approach to accounting for uncertainty in resource and environmental management decision-making.


Environmental decision-makers need to make explicit choices about regulating harmful activities, developing resources, and investing in restoration to meet biological, social and economic objectives across a broad range of stakeholder values. Decisions can be made via ad hoc approaches, usually in response to problems and conflicts as they arise, or by applying the formalism of structured decision-making that anticipates potential problems by explicitly considering objectives, alternative actions, uncertainties, and risks.


Upon completing Uncertainty, Risk, and Decision Analysis, students will have improved their thinking and decision-making skills in situations involving uncertainty and risk. Specific Learning Objectives in an environmental context include:

A) Uncertainty:
1. Identify and describe potential types and sources of uncertainty
2. Quantify uncertainty using Bayesian statistics

B) Risk:
3. Explain how uncertainty can create both risks and opportunities
4. Describe the four stages of risk analysis: perception, assessment, management, and communication
5. Explain the precautionary principle and the precautionary approach
6. Identify risk prone and risk averse behavioural types

C) Decision analysis:
7. Describe common decision traps
8. Construct simple quantitative decision analyses in MS Excel
9. Identify situations when taking uncertainty into account matters
10. Describe decision concepts including: mini-max/maxi-min decisions, value of information, Monte Carlo simulation, fragility/anti-fragility, and tail risks in environmental management


  • Participation in classes and weekly tutorials (10) 20%
  • Major project assignments (2) 50%
  • Term project and presentation 30%



1. All students will require a laptop in classes and tutorials. The SFU library has free, 4-hr loans of laptops:

  • https://www.lib.sfu.ca/borrow/borrowmaterials/laptops-equipment/borrow-laptop
  • The campus-wide demand for library laptops is high and the library often runs out quickly. If you need to use the library laptops, you should show-up early at the library check-out desk.

2. MS Excel installed on laptop prior to the first class.


Morgan, G. and M. Henrion. 1990. Uncertainty: A Guide to Dealing with Uncertainty in Quantitative Risk and Policy Analysis. Cambridge University Press, 332 pp.
A digital version of the text can be purchased at: http://www.sfu.ca/bookstore/coursematerials


Your personalized Course Material list, including digital and physical textbooks, are available through the SFU Bookstore website by simply entering your Computing ID at: shop.sfu.ca/course-materials/my-personalized-course-materials.

Registrar Notes:


SFU’s Academic Integrity website http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.

Each student is responsible for his or her conduct as it affects the university community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the university. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the university. http://www.sfu.ca/policies/gazette/student/s10-01.html