TÜRKÇE
ENGLISH
Information
| Code | ISB461 |
| Name | Simulation and Modelling |
| Term | 2024-2025 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 |
| Label | FE Field Education Courses E Elective |
| 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 essence fundamentals and concepts in the field of Statistics | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Emphasize the importance of Statistics in life | |
| PLO03 | Bilgi - Kuramsal, Olgusal | Define basic principles and concepts in the field of Law and Economics | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Produce numeric and statistical solutions in order to overcome the problems | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Use proper methods and techniques to gather and/or to arrange the data | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | |
| PLO08 | Bilgi - Kuramsal, Olgusal | Make statistical inference (estimation, hypothesis tests etc.) | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques and gain insight | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programs | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Distinguish the difference between the statistical methods | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Make oral and visual presentation for the results of statistical methods | |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have capability on effective and productive work in a group and individually | 2 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs | |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Develop scientific and ethical values in the fields of statistics-and scientific data collection |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Definitions and a review of probability and random variables | Lecture notes: Chapter 1 | |
| 2 | Random number generators | Lecture notes: Chapter 2, Reference book: p.123-140 and p.147-157 | |
| 3 | Simulating from some distributions - 1 | Lecture notes: Chapters 3.1 to 3.3, Reference book: Chapters 3.1, 3.5 and 3.6 | |
| 4 | Simulating from some distributions - 2 | Lecture notes: Chapters 3.1 to 3.3, Reference book: Chapters 3.1, 3.5 and 3.6 | |
| 5 | Algorithms and MATLAB | Lecture notes: Chapter 4 | |
| 6 | Generating random numbers and simulating some distributions with MATLAB | Lecture notes: Chapter 4 | |
| 7 | Monte Carlo experiment and simulation, estimation of a parameter with simulation | Lecture notes: Chapters 5.1 to 5.3, Reference book: p.246-250 | |
| 8 | Mid-Term Exam | A review of topics about the midterm exam | |
| 9 | Estimation of a parameter with simulation - 1 | Lecture notes: Chapter 5 | |
| 10 | Estimation of a parameter with simulation - 2 | Lecture notes: Chapter 5 | |
| 11 | Applications of simulation 1: Estimation of a parameter, estimation of a probability | Reference book: p.250-261 | |
| 12 | Applications of simulation 2: Estimation of a probability, hypothesis testing | Reference book: p.250-261 | |
| 13 | Applications of simulation 3: Hypothesis testing, simulating a regression equation | Lecture notes: Chapter 5 | |
| 14 | Applications of simulation 4: Simulating a regression equation, Monte Carlo Integral | Lecture notes: Chapter 5 | |
| 15 | Applications of simulation 5: Monte Carlo Integral | Lecture notes: Chapter 5 | |
| 16 | Term Exams | A review of topics about the final exam | |
| 17 | Term Exams | A review of topics about the final exam |
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 | ||