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COURSE UNIT TITLECOURSE UNIT CODESEMESTERTHEORY + PRACTICE (Hour)ECTS
MATHEMATICAL ECONOMICS II ECO344 - 3 + 0 5

TYPE OF COURSE UNITElective Course
LEVEL OF COURSE UNITBachelor's Degree
YEAR OF STUDY-
SEMESTER-
NUMBER OF ECTS CREDITS ALLOCATED5
NAME OF LECTURER(S). Servıs Servıs
LEARNING OUTCOMES OF THE COURSE UNIT At the end of this course, the students;
1) Should have become familiar with expression of linear programming models used in economics. Understands variables, constants, constraints and objective functions in linear programming models.
2) Should have become familiar with the solution and analysis methods used in economic models. Understands the simplex method, duality, sensitivity analysis and integer programming, Understands the solution of The Transportation Problem and similar problems.
3) Should have become familiar with basic game theory solution techniques and solution of some game theory problems using linear programming methods.
MODE OF DELIVERYFace to face
PRE-REQUISITES OF THE COURSENo
RECOMMENDED OPTIONAL PROGRAMME COMPONENTNone
COURSE DEFINITIONThis course examines mathematical techniques used in solving basic and intermediate micro and macro economic problems.
COURSE CONTENTS
WEEKTOPICS
1st Week Mathematical Models
2nd Week Linear Programming Model
3rd Week Simplex Method
4th Week duality
5th Week Sensitivity Analysis
6th Week Integer Programming
7th Week Transportation Problem
8th Week Midterm
9th Week Two people, Zero Sum Games
10th Week Other Topics in Game Theory
11th Week Other Topics in Game Theory
12th Week Other Topics in Game Theory
13th Week Other Topics in Linear Programming
14th Week Other Topics in Linear Programming
RECOMENDED OR REQUIRED READINGPaul R. Thie, An Introduction to Linear Programming and Game Theory, John Wiley & Sons 0-471-62488-8
PLANNED LEARNING ACTIVITIES AND TEACHING METHODSLecture,Discussion
ASSESSMENT METHODS AND CRITERIA
 QuantityPercentage(%)
Mid-term140
Total(%)40
Contribution of In-term Studies to Overall Grade(%)40
Contribution of Final Examination to Overall Grade(%)60
Total(%)100
ECTS WORKLOAD
Activities Number Hours Workload
Midterm exam111
Preparation for Quiz000
Individual or group work14342
Preparation for Final exam13030
Course hours14342
Preparation for Midterm exam12525
Laboratory (including preparation)000
Final exam111
Homework000
Total Workload141
Total Workload / 304,7
ECTS Credits of the Course5
LANGUAGE OF INSTRUCTIONEnglish
WORK PLACEMENT(S)No
  

KEY LEARNING OUTCOMES (KLO) / MATRIX OF LEARNING OUTCOMES (LO)
LO1LO2LO3
K1      X
K2      X
K3    X  
K4  X    
K5  X    
K6      X
K7      X
K8    X  
K9  X    
K10  X    
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K13