Decision Analysis

Recommended Prerequisites

NA

Teaching Methods

Classroom interaction:

- Presentation of the themes promoting debate (student-student and student-teacher).

- Solving (by students, individually or in small groups, or by the teacher) of cases that illustrate the practical relevance of the themes and different decision aiding strategies.

- Role-playing.

The presentation of the themes and the study of cases emphasize the motivation of the students for studying the themes being addressed, by using concrete examples (from newspapers, from employment opportunity ads). When opportune, the related research activities of the teacher are mentioned.

 

Evaluation:

- Written test – 80%.

- Individual applied work (solving a case) – 20%.

 

Although there are no formal office hours, students can meet the teacher outside the class in order to seek clarification and explanations, to debate a theme, or to seek guidance for the research assignment.

Learning Outcomes

O1. To avoid common biases in situations of uncertainty, identifying the corresponding heuristics.

O2. To know and apply the classical criteria for decision under uncertainty.

O3. To recognize that there are multiple methodologies for decision aiding under uncertainty, each one with its advantages and disadvantages, being able of sustaining which are more adequate in each situation.

O4. To recommend in which situations it is worthwhile to perform studies aimed at gathering additional information.

O5. To take part in sequential decision processes, either as a decision maker or as a consultant, by building appropriate models to guide the dialogue with intervening actors and to deal with uncertainty.

These learning outcomes contribute to develop several generic skills, namely those of critical reasoning, analysis and synthesis, problem solving, and information interpretation and management.

Work Placement(s)

No

Syllabus

This course presents classical Decision Analysis to deal with uncertainty based on the Bayesian approach and utility theory. This coherent theoretical framework for dealing with uncertainty and addressing subjectivity is presented, without neglecting behavioral aspects.

The main topics are:

1) Heuristics and biases

2) Classical criteria for decision under uncertainty

3) Decision trees and influence diagrams

4) Value of information

5) Expected utility theory.

Head Lecturer(s)

Luís Miguel Cândido Dias

Assessment Methods

Evaluation
Individual applied work (solving a case) : 20.0%
Written test : 80.0%

Bibliography

CLEMEN, Robert T. - Making hard decisions: an introduction to decision analysis. 2nd ed.. Pacific Grove: Duxbury Press, 1996. [BP 519.8 CLE].

GOODWIN, Paul; WRIGHT, George — Decision analysis for management judgment. Chichester: John Wiley & Sons, 2001. [BP 519.8 GOO]

RAIFFA, Howard — Decision analysis: introductory lectures on choices under uncertainty. New York: McGraw-Hill, 1976. [BP 519.8 RAI]

WINTERFELDT, Detlof von; EDWARDS, Ward — Decision analysis and behavioral research. Cambridge: Cambridge University Press, 1986. [BP 519.8 WIN]