1.5.2 Learn more

Course subject(s) Module 1. When and how to use SEJ?

Learn more about Module 1

During this module, you have been introduced to several topics which have been extensively researched over the years or other interesting concepts.

Here are some references to these topics. Enjoy!

Want to learn even more? Please feel to contact the course team!

“reading” by Terry Freedman is licensed under CC BY-NC-ND 2.0

Messaging uncertainty using verbal descriptions

Messaging uncertainty using verbal descriptions is a common approach, both in daily life as well as in more formal contexts. The topic has been the subject of many empirical research studies in the field of psychology, especially in the 90s.

If you are interested in reading more about this, here is a brief list of books and articles that you might find interesting:

  • Morgan, M. G., Henrion, M., & Small, M. (1990). Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis.Cambridge university press.
  • Carey, J. M., & Burgman, M. A. (2008). Linguistic uncertainty in qualitative risk analysis and how to minimize it. Annals of the New York Academy of Sciences1128(1), 13-17.
  • Handmer, John, and Beth Proudley. “Communicating uncertainty via probabilities: The case of weather forecasts.” Environmental Hazards7, no. 2 (2007): 79-87.
  • Gigerenzer, G., Hertwig, R., Van Den Broek, E., Fasolo, B., & Katsikopoulos, K. V. (2005). “A 30% chance of rain tomorrow”: How does the public understand probabilistic weather forecasts?. Risk Analysis: An International Journal25(3), 623-629.
  • Budescu, David V., Shalva Weinberg, and Thomas S. Wallsten. “Decisions based on numerically and verbally expressed uncertainties.” Journal of Experimental Psychology: Human Perception and Performance14, no. 2 (1988): 281.
  • Heath, Chip, and Amos Tversky. “Preference and belief: Ambiguity and competence in choice under uncertainty.” Journal of risk and uncertainty4, no. 1 (1991): 5-28.
  • Rapoport, Amnon, Thomas S. Wallsten, Ido Erev, and Brent L. Cohen. “Revision of opinion with verbally and numerically expressed uncertainties.” Acta Psychologica74, no. 1 (1990): 61-79.
  • Wallsten, T. S., & Budescu, D. V. (1995). A review of human linguistic probability processing: General principles and empirical evidence. The Knowledge Engineering Review10(1), 43-62.
  • Windschitl, P. D., & Wells, G. L. (1996). Measuring psychological uncertainty: Verbal versus numeric methods. Journal of Experimental Psychology: Applied2(4), 343.
  • Pardowitz, T., Kox, T., Göber, M., & Bütow, A. (2015). Human estimates of warning uncertainty: Numerical and verbal descriptions. Mausam66, 625-634.

Uncertainty quantification

Uncertainty quantification is the field which aims to characterize and quantify the existing uncertainties in a world governed by randomness, hence with a stochastic nature. Uncertainty quantification is therefore ubiquitous in numerous is not all science fields. You can find numerous literature available within each specific field, from Computational Science and Engineering to Social Sciences.

You might recall that Anca mentioned the “aleatory variability” and “epistemic uncertainty”. An excellent read on the role of operational definitions in representing uncertainty is Roger Cooke’s paper on the anatomy of a squizzel.

Red Team / Blue Team Climate wars

If you are interested to read more about the red team/blue team approach to climate change debate in the U.S., here are two interesting reads:



Creative Commons License
Decision Making Under Uncertainty: Introduction to Structured Expert Judgment by TU Delft OpenCourseWare is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Based on a work at https://online-learning.tudelft.nl/courses/decision-making-under-uncertainty-introduction-to-structured-expert-judgment//.
Back to top