COURSE INTRODUCTION AND APPLICATION INFORMATION


Course Name
Quantitative Methods
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
EBA 503
Fall/Spring
3
0
3
5
Prerequisites
None
Course Language
English
Course Type
Service Course
Course Level
Second Cycle
Mode of Delivery -
Teaching Methods and Techniques of the Course
Course Coordinator
Course Lecturer(s)
Assistant(s)
Course Objectives This course aims at teaching a variety of management science methods useful in solving management problems in many areas such as Marketing, Finance, and Production so that the students can gain a quantitative foundation in basic mathematical modeling and problem solving that will be helpful in the higher level courses such as Operations Management and Production Planning and Inventory Control.
Learning Outcomes The students who succeeded in this course;
  • Define basic mathematical modeling concepts and techniques
  • Formulate a variety of management problems in marketing, production and finance
  • Apply basic mathematical optimization models including linear programming and integer programming
  • Interpret the computer output generated from “QM for Windows” to solve linear programming models.
  • Analyze various decision making problems under certainty, uncertainty and risk.
Course Description The main emphasis of the course is how to model a managerial problem using mathematical modeling (Linear programming and Integer programming). Many examples from different application areas are given.
Related Sustainable Development Goals

 



Course Category

Core Courses
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Required Materials
1 Introduction to Management Science Chapter 1 of the Text Book
2 Linear Programming: Model Formulation and Graphical Solution Chapter 2 of the Text Book
3 Linear Programming: Computer Solution and Sensitivity Analysis Chapter 3 of the Text Book
4 Linear Programming: Modeling Examples Chapter 4 of the Text Book
5 Linear Programming: Modeling Examples Chapter 4 of the Text Book
6 Integer Programming Chapter 5 of the Text Book
7 Integer Programming Chapter 5 of the Text Book
8 MIDTERM EXAM & Transportation, Transshipment and Assignment Problems Chapter 6 of the Text Book
9 Transportation, Transshipment and Assignment Problems Chapter 6 of the Text Book
10 Network Flow Problems Chapter 7 of the Text Book
11 Project Management Chapter 8 of the Text Book
12 Project Management Chapter 8 of the Text Book
13 Decision Analysis Chapter 12 of the Text Book
14 Decision Analysis Chapter 12 of the Text Book
15 Review of the Semester
16 Review of the Semester  
Course Notes/Textbooks

Introduction to Management Science. Bernard W. Taylor III, Twelfth Edition, Prentice Hall, New Jersey ISBN-13: 978-0133778847

Power points of the textbook are used. The class notes will be posted online before the class

Suggested Readings/Materials

Operations Research Applications and Algorithms, Wayne L. Winston, Fourth Edition, Thomson Books  ISBN-13: 978-0534380588

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
1
5
Laboratory / Application
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterm
1
15
Final Exam
1
80
Total

Weighting of Semester Activities on the Final Grade
2
20
Weighting of End-of-Semester Activities on the Final Grade
1
80
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: 16 x total hours)
16
Study Hours Out of Class
15
6
90
Field Work
Quizzes / Studio Critiques
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exam
Midterms
1
20
Final Exams
1
32
    Total
190

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest