Information
Code | IEM762 |
Name | Simulation |
Term | 2024-2025 Academic Year |
Term | Fall and Spring |
Duration (T+A) | 3-0 (T-A) (17 Week) |
ECTS | 6 ECTS |
National Credit | 3 National Credit |
Teaching Language | Türkçe |
Level | Yüksek Lisans Dersi |
Type | Normal |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | Prof. Dr. HÜSEYİN GÜLER |
Course Instructor |
1 |
Course Goal / Objective
The aim of this course is to provide the students with the knowledge of simulation that is necessary in statistics and econometrics. It is difficult to solve some problems in these fields analytically. To solve these problems, the simulation method which includes a virtual experiment can be used. In this context, the definition and contents of simulation, techniques used in simulation and mathematical modelling is considered. It is also necessary to use a programming language to simulate an event with a mathematical model. Therefore, the logic behind the alghoritms and MATLAB program is also discussed in the course. Following these topics, Monte Carlo models of some events are investigated to gain practice for students.
Course Content
The course covers random number generators, inverse transform method, simulation in some discrete and continuous distributions, virtual experiment, Monte Carlo estimation, Monte Carlo estimates for moments, Monte Carlo integration, estimating probabilities with Monte Carlo, estimating the size and power of a test, finding critical values with Monte Carlo, simulation in regression models, simulation in time series, the bootstrap method.
Course Precondition
None
Resources
İstatistiksel Simülasyon Ders Notları, Dr. Hüseyin GÜLER, Adana, 2015.
Notes
Benzetim, Çevirenler: Mustafa Yavuz Ata, M. Akif Bakır, Osman Ufuk Ekiz, Nobel Kitabevi, 2015. Matematiksel Modelleme ve Simülasyon, Fikri ÖZTÜRK, Levent ÖZBEK, Gazi Kitabevi, Ankara, 2004. A Course in Simulation, Sheldon M. Ross, Macmillan, New York, 1990. Simulation: A Statistical Perspective, J. P.C. Kleijnen ve W. van Groenendaal, John Wiley, 1992. Simulation Modelling & Analysis, A. Law ve W. Kelton, McGraw-Hill, 1991. An Introduction to the Bootstrap, B. Efron ve R.J. Tibshirani, Chapman & Hall, 1993.
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | Creates the mathematical model of an event |
LO02 | Writes an algorithm to solve the mathematical model with simulation |
LO03 | Codes the written algorithm in a programming language |
LO04 | Chooses virtual samples from the distribution of random variables |
LO05 | Defines the consistent Monte carlo estimators of the model parameters |
LO06 | Obtains Monte Carlo estimates for parameters |
LO07 | Performs a bootstrap to estimate model parameters |
Relation with Program Learning Outcome
Order | Type | Program Learning Outcomes | Level |
---|---|---|---|
PLO01 | Bilgi - Kuramsal, Olgusal | Explains contemporary concepts about Econometrics, Statistics, and Operation Research | 5 |
PLO02 | Bilgi - Kuramsal, Olgusal | Explains relationships between acquired knowledge about Econometrics, Statistics, and Operation Research | 4 |
PLO03 | Bilgi - Kuramsal, Olgusal | Explains how to apply acquired knowledge in the field to Economics, Business, and other social sciences | |
PLO04 | Beceriler - Bilişsel, Uygulamalı | Performs conceptual analysis to develop solutions to problems | |
PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 5 |
PLO06 | Beceriler - Bilişsel, Uygulamalı | Interprets the results obtained from the most appropriate method to predict the model | 4 |
PLO07 | Beceriler - Bilişsel, Uygulamalı | Synthesizes the information obtained by using different sources within the framework of academic rules in a field that does not research | |
PLO08 | Beceriler - Bilişsel, Uygulamalı | Uses acquired knowledge in the field to determine the vision, aim, and goals for an organization/institution | |
PLO09 | Beceriler - Bilişsel, Uygulamalı | Searches for new approaches and methods to solve problems being faced | |
PLO10 | Beceriler - Bilişsel, Uygulamalı | Presents analysis results conveniently | |
PLO11 | Beceriler - Bilişsel, Uygulamalı | Collects/analyzes data in a purposeful way | |
PLO12 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Converts its findings into a master's thesis or a professional report in Turkish or a foreign language | |
PLO13 | Beceriler - Bilişsel, Uygulamalı | Develops solutions for organizations using Econometrics, Statistics, and Operation Research | 4 |
PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Performs an individual work to solve a problem with Econometrics, Statistics, and Operation Research | 4 |
PLO15 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | |
PLO16 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in the field of study | |
PLO17 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research or writes a new code | 5 |
PLO18 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Interprets the feelings, thoughts and behaviors of the related persons correctly/expresses himself/herself correctly in written and verbal form | |
PLO19 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on economic and social events by following current issues | |
PLO20 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Basic concepts, a review of probability and random variables | A review of probability and random variables from some reference books | Öğretim Yöntemleri: Anlatım |
2 | Probability-integral transformation and random number generators | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
3 | Inverse transformation method, simulation in some discrete and continuous distributions | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
4 | Simulation in some discrete and continuous distributions | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim |
5 | Virtual experiment, Monte Carlo estimation | Lecture notes, reference books, Paper: Usta, Cirak ve Hileli Zar | Öğretim Yöntemleri: Anlatım, Tartışma, Benzetim, Problem Çözme |
6 | Monte Carlo estimates of moments | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim |
7 | Monte Carlo integration | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
8 | Mid-Term Exam | A review for the exam | Ölçme Yöntemleri: Proje / Tasarım |
9 | Estimating probabilities with Monte Carlo experiment | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim |
10 | Monte Carlo estimate of the parameter pi | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim |
11 | Estimate of the size and power of a test | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Benzetim, Problem Çözme |
12 | Finding critical values with Monte Carlo method | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
13 | Simulation in a regression model | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
14 | Simulation in time series | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
15 | Bootstrapping | Lecture notes, reference books | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
16 | Term Exams | A review for the exam | Ölçme Yöntemleri: Yazılı Sınav |
17 | Term Exams | A review for the exam | Ölçme Yöntemleri: Yazılı Sınav |
Student Workload - ECTS
Works | Number | Time (Hour) | Workload (Hour) |
---|---|---|---|
Course Related Works | |||
Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
Assesment Related Works | |||
Homeworks, Projects, Others | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
Final Exam | 1 | 30 | 30 |
Total Workload (Hour) | 157 | ||
Total Workload / 25 (h) | 6,28 | ||
ECTS | 6 ECTS |