COURSE UNIT TITLE

: GAME THEORY

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
STA 5082 GAME THEORY ELECTIVE 3 0 0 8

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

ASSOCIATE PROFESSOR UMAY ZEYNEP UZUNOĞLU KOÇER

Offered to

Statistics
Statistics
STATISTICS

Course Objective

The aim of this course is to express and solve the decision problem in between two opponent decision makers. It is aimed that the students will gain knowledge about the formulation and solution concepts of two-player games with complete information.

Learning Outcomes of the Course Unit

1   Defining basic concepts about game theory
2   Expressing a situation as a static or a dynamic game
3   Performing implementations and analysis on static and dynamic games with complete information
4   Interpreting the results of the analysis
5   Making suggestions to the decision makers that optimize their situation
6   Reviewing recent literature about two-player static and dynamic games with complete information and presenting examples

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Introduction to game theory, basic concepts
2 Static games with complete information, games with strategic form, pure strategy, dominance
3 Definition of Nash equilibrium, existence and characteristics of Nash equilibrium, examples
4 Best response function
5 Definition of mixed-strategy, expected utility, mixed strategies and dominance, mixed strategy Nash equilibrium
6 Mixed strategies and continuous payoffs, existence of Nash equilibrium in mixed strategies, correlated equilibrium
7 MIDTERM
8 Dynamic games with complete information, definition of dynamic games, history and history set
9 Definition of extensive form games, pure strategies in extensive form games, the relation between extensive form and strategic form, Presentation
10 The equilibrium of extensive form games, backward induction, Presentation
11 Subgame perfect equilibrium, mixed and behavior strategies
12 Applications of subgame perfect Nash equilibrium, Homework
13 Observable multi-stage games, definition and examples, Homework
14 The applications of observable multi-stage games

Recomended or Required Reading

Textbook(s):
D. Fudenberg, J. Tirole, 1991, Game Theory, MIT Press, England.

References:
E. Yılmaz, 2009, Oyun Teorisi, Literatür Yayınları, Türkiye.

Materials: None

Planned Learning Activities and Teaching Methods

Lecture, problem solving, homework, presentation.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 ASG ASSIGNMENT
3 PRS PRESENTATION
4 FIN FINAL EXAM
5 FCG FINAL COURSE GRADE MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + FIN * 0.40
6 RST RESIT
7 FCGR FINAL COURSE GRADE (RESIT) MTE* 0.30 + ASG * 0.20 + PRS * 0.10 + RST * 0.40


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Evaluation of midterm, presentation, homework, and final exam.

Language of Instruction

English

Course Policies and Rules

Student responsibilities:
Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy.

Contact Details for the Lecturer(s)

DEU Fen Fakültesi Istatistik Bölümü
e-mail: umay.uzunoglu@deu.edu.tr
Tel: 0232 301 85 60

Office Hours

It will be announced when the course schedule of the faculty is determined.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparing presentations 2 20 40
Preparations before/after weekly lectures 14 4 56
Preparing assignments 2 20 40
Preparation for midterm exam 1 8 8
Preparation for final exam 1 10 10
Final 1 2 2
Midterm 1 2 2
TOTAL WORKLOAD (hours) 200

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10
LO.15
LO.254445
LO.3444
LO.44455
LO.5555
LO.6555