COURSE INFORMATION
Course CodeCourse TitleL+P HourSemesterECTS
BUSI 323DECISION ANALYSIS3 + 05th Semester5

COURSE DESCRIPTION
Course Level Bachelor's Degree
Course Type Elective
Course Objective To develop an understanding of Advanced Decision Making Techniques to solve the decisionmaking problems that confronts and confounds managers in both the public and the private sector by developing mathematical models of those problems.
Course Content Advanced Topics in linear programming, nonlinear programming, game theory, goal programming, deterministic dynamic programming, probabilistic dynamic programming, simulation.
Prerequisites No prerequisites.
Corequisite No corequisites.
Mode of Delivery Face to face

COURSE LEARNING OUTCOMES
1to analyze the complex administrative problems and apply the systems approach
2To have a solid understanding of basic Management Science concepts
3To develop mathematical models for a variety of management problems that they come across in public and private industry
4To solve complex mathematical models by means of computer softwares
5To interpret the solutions of the models for daily practical use of business managers

COURSE'S CONTRIBUTION TO PROGRAM
Data not found.

ECTS ALLOCATED BASED ON STUDENT WORKLOAD BY THE COURSE DESCRIPTION
ActivitiesQuantityDuration (Hour)Total Work Load (Hour)
Course Duration14342
Hours for off-the-classroom study (Pre-study, practice)13339
Assignments11010
Mid-terms11313
Final examination12626
Total Work Load

ECTS Credit of the Course






130

5

COURSE DETAILS
 Select Year   


 Course TermNoInstructors
Details 2018-2019 Fall1HÜSEYİN KOÇAK

Course Details
Course Code:  BUSI 323 Course Title:  DECISION ANALYSIS
L+P Hour : 3 + 0   Course Code : 1   Language Of Instruction: English Course Semester :  2018-2019 Fall
Course Coordinator :  ASSISTANT PROFESSOR HÜSEYİN KOÇAK E-Mail:  Phone Number :  296 2654, 296 3859,
Course Location İİBF C0304,
Goals : To develop an understanding of Advanced Decision Making Techniques to solve the decisionmaking problems that confronts and confounds managers in both the public and the private sector by developing mathematical models of those problems.
Content : Advanced Topics in linear programming, nonlinear programming, game theory, goal programming, deterministic dynamic programming, probabilistic dynamic programming, simulation.
Attendance : %70
Topics
WeeksTopics
1 Introduction
2 Decision making and the steps of the decision-making process
3 The types of decision-making environments
4 Decision Making under Uncertainty
5 Decision Making under Risk
6 Minimization Problem
7 Decision Trees
8 Midterm Exam
9 Using Software in Decision Analysis (QM)
10 Bayesian Analysis
11 Bayesian Analysis (cont.)
12 Utility Theory
13 Utility Theory (cont.)
14 The Practical Application of Decision Analysis
Materials
Materials are not specified.
Resources
ResourcesResources Language
Barry Render, Ralph M. Stair and Michael E. Hanna, Quantitative Analysis for Management, 12/E, Pearson Higher Education, 2015.English
Hamdy A. Taha, Operations Research: An Introduction, Eight Edition, Pearson Education, 2007.English
Frederick S. Hillier and Gerald J. Lieberman, Introduction to Operations Research, Ninth Edition, McGraw-Hill, 2010.English
Bernard W. Taylor III, Introduction to Management Science, 11th Edition, Pearson, 2013.English
Course Assessment
Assesment MethodsPercentage (%)Assesment Methods Title
Final Exam60Final Exam
Midterm Exam40Midterm Exam
L+P: Lecture and Practice
PQ: Program Learning Outcomes
LO: Course Learning Outcomes