ISyE 516: Introduction to Decision Analysis

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ISyE 516 - Introduction to Decision Analysis

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ISYE 516 Intro to Decision Analysis, Fall08 (Bier) Sections: 001

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ISYE 516: Introduction to Decision Analysis, Spring 2005 (Bier), formerly Course Homepage of Bier

ISYE 516: Introduction to Decision Analysis, Fall 2003 (Nembhard)

ISYE 516: Introduction to Decision Analysis, Fall 1998 (Sainfort)

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Catalog Description

516 Introduction to Decision Analysis. II; 3 cr. Overview of modeling techniques and mehtods used in decision analysis, including multiattribute utility models, decision trees, and Bayesian models. Psychological components of decision making are discussed. Elicitation techniques for model building are emphasized. Practical applications through real world model building are described and conducted. P: Stat 311 or Math 431 or cons inst.

Course Prerequisite(s)

See catalog description above.

Prerequisite knowledge and/or skills

Probability theory
Common probability distributions(normal,binomial,poisson, exponential, beta, gamma)
Bayes Theorem
Basic calculus

Textbook(s) and/or other required material

R.T. Clemen and T. Reilly, "Making Hard Decisions with Decision Tools and Suite," Duxbury Press, 2000.

Course objectives

This course will develop student knowledge of: basic decision analysis concepts, the value of using decision analysis methods to aid in practical decision making; and techniques; the contextual considerations in decision making.

Topics covered

Elements of decision problems
structuring decision problems
decision trees
influence diagrams
sensitivity analysis
subjective probability
value of information
risk preferences
subjective probability
value functions
utility functions
multiattribute utility theory

Class/laboratory schedule

2 sessions per week of 75 minutes each.

Contribution of course to meeting the professional component

This course contributes primarily to the students' knowledge of engineering topics, and does provide design experience.

The following statement indicates which of the following considerations are included in this course: economic, environmental, ethical, political, societal, health and safety, manufacturability, sustainability.

economic societal health and safety

Relationship of course to undergraduate degree program objectives and outcomes

This course primarily serves students in the department. The information below describes how the course contributes to the undergraduate program objectives.

Use computer tools such as simulation and spreadsheets Know what information is necessary and sufficient to solve industrial engineering problems Have a working knowledge of data collection and analysis Recognize, describe, predict, and analyze systems behavior Design a system, component, or process to meet an identified need Integrate problem solutions into a proposed action program or plan Select and evaluate off-the-shelf solutions and vendors' proposals Maintain a systems level perspective, yet have an appreciation for product design and operational level issues Identify opportunities for improvement Communicate effectively and work well on teams Write clearly and grammatically Be proficient in technical communication including graphics Justify, communicate and sell a solution at all levels, both technical and nontechnical Understand contemporary issues and the impact of industrial engineering solutions in a global/societal context.

Assessment of student progress toward course objectives

Testing of knowledge of basic skills through homework, midterms, and a final exam
Student collaboration on open-ended problems

Copyright 2007 The Board of Regents of the University of Wisconsin System
Date last modified: 28-Dec-2007
Content by: prpeters@engr.wisc.edu
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