Information
Code | EKMS405 |
Name | Statistical Simulation |
Term | 2023-2024 Academic Year |
Semester | 7. Semester |
Duration (T+A) | 3-0 (T-A) (17 Week) |
ECTS | 5 ECTS |
National Credit | 3 National Credit |
Teaching Language | Türkçe |
Level | Lisans Dersi |
Type | Normal |
Mode of study | Yüz Yüze Öğretim |
Catalog Information Coordinator | Prof. Dr. HÜSEYİN GÜLER |
Course Instructor |
Prof. Dr. HÜSEYİN GÜLER
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
The aim of this course is to provide students with the knowledge of modelling analytically difficult problems encountered in Statistics. In addition to this, it is also aimed to bring the knowledge of obtaining an empirical solution of the problem with a simulation by creating a virtual experiment.
Course Content
The definition and objective of simulation, techniques for simulation, mathematical modelling, programming in MATLAB, Monte Carlo estimation of a parameter of interest.
Course Precondition
None
Resources
İstatistiksel Simülasyon Ders Notları, Hüseyin Güler, Adana, 2015.
Notes
Benzetim, Beşinci Basımdan Çeviri, Sheldon Ross, Çevirenler: Mustafa Yavuz Ata, M. Akif Bakır, Osman Ufuk Ekiz, Nobel Kitabevi, 2015. Matematiksel Modelleme ve Simülasyon, Fikri Öztürk, Levent Özbek, Gazi Kitabevi, 2004.
Course Learning Outcomes
Order | Course Learning Outcomes |
---|---|
LO01 | Students will be able to determine the difference between classical sampling approaches and simulation. |
LO02 | Students will be able to generate random numbers from the uniform distribution within range (0,1) with random number generators. |
LO03 | Students will be able to determine how they can generate random numbers from a distribution with probability integral transformation. |
LO04 | Students will be able to model a real life phenomena with random variables. |
LO05 | Students will be able to determine how they can estimate the model parameters with simulation. |
LO06 | Students will be able to estimate the parameters of a large scale problem with simulations by using MATLAB. |
Relation with Program Learning Outcome
Order | Type | Program Learning Outcomes | Level |
---|---|---|---|
PLO01 | Bilgi - Kuramsal, Olgusal | Explain the basic concepts and theorems in the fields of Econometrics, Statistics and Operations research | 4 |
PLO02 | Bilgi - Kuramsal, Olgusal | Acquires basic Mathematics, Statistics and Operation Research concepts | 4 |
PLO03 | Bilgi - Kuramsal, Olgusal | Describes the necessary concepts of Business | |
PLO04 | Beceriler - Bilişsel, Uygulamalı | Equipped with the foundations of Economics, and develops Economic models | |
PLO05 | Beceriler - Bilişsel, Uygulamalı | Models problems with Mathematics, Statistics, and Econometrics | 4 |
PLO06 | Beceriler - Bilişsel, Uygulamalı | Has the ability to analyze/interpret at the conceptual level to develop solutions to problems | |
PLO07 | Beceriler - Bilişsel, Uygulamalı | Collects/analyses data | |
PLO08 | Beceriler - Bilişsel, Uygulamalı | Interprets the results analyzed with the model | 3 |
PLO09 | Beceriler - Bilişsel, Uygulamalı | Combines the information obtained from different sources within the framework of academic rules in a field which does not research | |
PLO10 | Beceriler - Bilişsel, Uygulamalı | It develops traditional approaches, practices and methods into new working methods when it deems necessary | |
PLO11 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Leads by taking responsibility individually and/or within the team | 2 |
PLO12 | Yetkinlikler - Öğrenme Yetkinliği | In addition to herself/himself professional development, constantly improves in scientific, cultural, artistic and social fields in line with interests and abilities | |
PLO13 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the necessity of lifelong learning, it constantly renews itself by following the current developments in its field. | |
PLO14 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses a package program of Econometrics, Statistics, and Operation Research | 4 |
PLO15 | Yetkinlikler - İletişim ve Sosyal Yetkinlik | Uses Turkish and at least one other foreign language, academically and in the business context | |
PLO16 | 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 | |
PLO17 | Yetkinlikler - Alana Özgü Yetkinlik | Interprets data on current economic and social issues | |
PLO18 | Yetkinlikler - Alana Özgü Yetkinlik | Applies social, scientific and professional ethical values |
Week Plan
Week | Topic | Preparation | Methods |
---|---|---|---|
1 | Definitions and a review of probability and random variables | Lecture notes: Chapter 1 | Öğretim Yöntemleri: Anlatım |
2 | Random number generators | Lecture notes: Chapter 2, Reference book: p.123-140 and p.147-157 | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama |
3 | Simulating from some distributions - 1 | Lecture notes: Chapters 3.1 to 3.3, Reference book: Chapters 3.1, 3.5 and 3.6 | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim |
4 | Simulating from some distributions - 2 | Lecture notes: Chapters 3.1 to 3.3, Reference book: Chapters 3.1, 3.5 and 3.6 | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim |
5 | Algorithms and MATLAB | Lecture notes: Chapter 4 | Öğretim Yöntemleri: Anlatım, Soru-Cevap, Alıştırma ve Uygulama, Problem Çözme |
6 | Generating random numbers and simulating some distributions with MATLAB | Lecture notes: Chapter 4 | Öğretim Yöntemleri: Anlatım, Alıştırma ve Uygulama, Benzetim, Problem Çözme |
7 | Monte Carlo experiment and simulation, Parameter estimation with simulation | Lecture notes: Chapters 5.1 to 5.3, Reference book: p.246-250 | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama, Problem Çözme |
8 | Mid-Term Exam | General review for the midterm exam | Ölçme Yöntemleri: Yazılı Sınav |
9 | Estimation of a parameter with simulation - 1 | Lecture notes: Chapter 5 | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
10 | Estimation of a parameter with simulation - 2 | Lecture notes: Chapter 5 | Öğretim Yöntemleri: Anlatım, Tartışma, Alıştırma ve Uygulama |
11 | Applications of simulation 1: Estimation of a parameter, estimation of a probability | Reference book: p.250-261 | Öğretim Yöntemleri: Anlatım, Tartışma, Grup Çalışması, Proje Temelli Öğrenme |
12 | Applications of simulation 2: Estimation of a probability, hypothesis testing | Reference book: p.250-261 | Öğretim Yöntemleri: Anlatım, Tartışma, Grup Çalışması, Proje Temelli Öğrenme |
13 | Applications of simulation 3: Hypothesis testing, simulating a regression equation | Lecture notes: Chapter 5 | Öğretim Yöntemleri: Anlatım, Tartışma, Grup Çalışması, Proje Temelli Öğrenme |
14 | Applications of simulation 4: Simulating a regression equation, Monte Carlo Integral | Lecture notes: Chapter 5 | Öğretim Yöntemleri: Anlatım, Tartışma, Grup Çalışması, Proje Temelli Öğrenme |
15 | Applications of simulation 5: Monte Carlo Integral | Lecture notes: Chapter 5 | Öğretim Yöntemleri: Anlatım, Tartışma, Grup Çalışması, Proje Temelli Öğrenme |
16 | Term Exams | General review for the final exam | Ölçme Yöntemleri: Yazılı Sınav |
17 | Term Exams | General review for the final 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 | 3 | 42 |
Assesment Related Works | |||
Homeworks, Projects, Others | 0 | 0 | 0 |
Mid-term Exams (Written, Oral, etc.) | 1 | 12 | 12 |
Final Exam | 1 | 18 | 18 |
Total Workload (Hour) | 114 | ||
Total Workload / 25 (h) | 4,56 | ||
ECTS | 5 ECTS |