GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
SİMULATİON TECHNİQUES/5331303
Course Title: SİMULATİON TECHNİQUES
Credits 3 ECTS 7.5
Course Semester 1 Type of The Course Elective
COURSE INFORMATION
 -- (CATALOG CONTENT)
 -- (TEXTBOOK)
 -- (SUPPLEMENTARY TEXTBOOK)
 -- (PREREQUISITES AND CO-REQUISITES)
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- COURSE OBJECTIVES
 -- COURSE LEARNING OUTCOMES
• Ability to design and to implement a virtual experiment in the statistical programming language R to obtain the Monte Carlo estimates.
 -- MODE OF DELIVERY
  The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE
1. Week  Introduction: Virtual and actual world.
2. Week  Scientific Modelling: Systems, random variables as inputs and outputs of a system, parameters vs statistics.
3. Week  Monte Carlo Estimation: Direct estimation of parameters via the Law of Large Numbers.
4. Week  General Methods of Generating Virtual Observations: Inverse transformation technique, acceptance-rejection technique.
5. Week  Generating Pseudo Random Numbers and Some Tests of Randomness.
6. Week  Fundamental Elements of R Programming Language.
7. Week  Midterm Exam.
8. Week  Random Sampling from Discrete Probability Distributions.
9. Week  Random Sampling from Continuous Probability Distributions.
10. Week  Discrete Event Simulation.
11. Week  Stopping Rules for a Simulation Run.
12. Week  Efficient Monte Carlo Estimators.
13. Week  Designing and Implementing Virtual Experiments in R Programming Environment.
14. Week  A Sample Monte Carlo Study on Robustness of z and t Statistics.
15. Week  Validating a Monte Carlo Study.
16. Week  Final Exam
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
1
20
 Assignment
8
10
 Application
0
0
 Projects
1
10
 Practice
0
0
 Quiz
0
0
 Percent of In-term Studies  
40
 Percentage of Final Exam to Total Score  
60
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
0
0
 Reading Tasks
14
4
56
 Searching in Internet and Library
14
1
14
 Material Design and Implementation
8
3
24
 Report Preparing
8
3
24
 Preparing a Presentation
2
3
6
 Presentation
2
1
2
 Midterm Exam and Preperation for Midterm Exam
1
10
10
 Final Exam and Preperation for Final Exam
1
10
10
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
188
 TOTAL WORKLOAD / 25: 
7.52
 Course Credit (ECTS): 
7.5
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
 PROGRAM LEARNING OUTCOMES
1
2
3
4
5
11. Based on the capabilities of undergraduate level, the students enrolled to the program can develop and deepen their knowledge and skill at the level of expertise on the same field of the undergradute study or a different field.X
22. The students use their theoretical and practical knowledge at the level of expertise in the area of statistics.X
33. The students should evaluate their acquired knowledge and skills in a critical perspective and the critical point of view guides their learning process.X
44. Theoretical and practical knowledge gained in graduate level in the field of Statistics should be applied and transfer to the current problems.X
55. By performing the process from the identification of the scientific research problem to reporting and the process should be transferred in oral, written and visual ways.X
66. The students should use computer software and information technologies on the level required by the field of Statistics.X
77. The students should have the ability to use Statistics in interdisciplinary studies.X
88. The students should have enough foreign language level to pursue statistical literature.X
99. At the required level of field of statistics, he/she should use statistical software and information technology efficiently in a such a way that helps solving problems in his/her research.X
1010. In the process of applying knowledge in a professional sense, social, scientific, and ethical values should be regarded.X
 -- NAME OF LECTURER(S)
   (Doç. Dr. Meltem EKİZ , Dr. Öğr. Üyesi Osman Ufuk EKİZ)
 -- WEB SITE(S) OF LECTURER(S)
   (http://websitem.gazi.edu.tr/site/yavuzata; http://websitem.gazi.edu.tr/site/myata; http://istatistikseliletisim.net)
 -- EMAIL(S) OF LECTURER(S)
   (ufukekiz@gazi.edu.tr)