BUSINESS ADMINISTRATION
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Course Introduction and Application Information

Course Code	Course Name	Semester	Theoretical	Practical	Credit	ECTS
ISM5206	Decision Analysis	Spring Fall	3	0	3	12

This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester.

Basic information

Language of instruction:	Turkish
Type of course:	Non-Departmental Elective
Course Level:	Bachelor’s Degree (First Cycle)
Mode of Delivery:	Face to face
Course Coordinator :	Instructor ÖZLEM KANGA
Course Lecturer(s):	Assoc. Prof. SEROL BULKAN
Recommended Optional Program Components:	N.A.
Course Objectives:	The aim of the course is to introduce the graphical models used in decision analysis and to provide a set of systematic tools to help the decision maker in giving a decision.

Learning Outcomes

The students who have succeeded in this course;
- Recognize the graphical models used in decision analysis.
- Model a given uncertain situation with Bayes networks.
- Compute exact and approximate inferences in Bayes networks.
- Model a given uncertain decision problem with influence diagrams.
- Make inferences in decision networks.
- Compute value of information.

Course Content

Expected Utility, Causal and Bayesian networks, Exact inference in Bayesian networks, Approximate inference in Bayesian networks, Learning Bayesian networks, Influence and decision networks, Value of information

Weekly Detailed Course Contents

Week	Subject	Related Preparation
1)	Probability review
2)	Expected Utility
3)	Causal and Bayesian networks
4)	Building Bayesian models
5)	Exact inference in Bayesian networks
6)	Exact inference in Bayesian networks
7)	Approximate inference in Bayesian networks
8)	Approximate inference in Bayesian networks
9)	Midterm exam
10)	Learning Bayesian networks
11)	Influence and decision networks
12)	Influence and decision networks
13)	Value of information
14)	Project presentations

Sources

Course Notes / Textbooks:	F.V. Jensen, 2001. Bayesian networks and decision graphs, New York : Springer
References:	Robert T. Clemen, 1996. Making Hard Decisions: An Introduction to Decision Analysis, 2nd edition, Duxbury Press

Evaluation System

Semester Requirements	Number of Activities	Level of Contribution
Homework Assignments	4	% 10
Project	1	% 20
Midterms	1	% 30
Final	1	% 40
Total		% 100
PERCENTAGE OF SEMESTER WORK		% 40
PERCENTAGE OF FINAL WORK		% 60
Total		% 100

ECTS / Workload Table

Activities	Number of Activities	Duration (Hours)	Workload
Course Hours	14	3	42
Study Hours Out of Class	14	2	28
Presentations / Seminar	1	10	10
Project	1	40	40
Homework Assignments	4	10	40
Midterms	1	15	15
Final	1	20	20
Total Workload			195

Contribution of Learning Outcomes to Programme Outcomes

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

	Program Outcomes	Level of Contribution
1)	Being able to identify problems and ask right questions
2)	Having problem solving skills and developing necessary analytical attitude
3)	Comprehending theoretical arguments along with counter arguments in detail
4)	Gaining awareness of lifelong learning and being qualified for pursuing graduate education
5)	Applying theoretical concepts in project planning
6)	Communicating efficiently by accepting differences and carrying out compatible teamwork
7)	Increasing efficiency rate in business environment
8)	Developing innovative and creative solutions in face of uncertainty
9)	Researching to gather information for understanding current threats and opportunities in business
10)	Being aware of the effects of globalization on society and business while deciding
11)	Possessing digital competence and utilizing necessary technology
12)	Communicating in at least one foreign language in academic and daily life
13)	Possessing managing skills and competence
14)	Deciding with the awareness of the legal and ethical consequences of business operations
15)	Expressing opinions that are built through critical thinking process in business and academic environment