ISB471 Econometric Models

4 ECTS - 3-0 Duration (T+A)- 7. Semester- 3 National Credit

Information

Code ISB471
Name Econometric Models
Term 2023-2024 Academic Year
Semester 7. Semester
Duration (T+A) 3-0 (T-A) (17 Week)
ECTS 4 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. MAHMUDE REVAN ÖZKALE
Course Instructor Prof. Dr. SADULLAH SAKALLIOĞLU (A Group) (Ins. in Charge)


Course Goal / Objective

Use of mathematical techniques that are required for matrix operations and use matrix operations to solve problems that may arise in various fields such as statistics

Course Content

Matrix operations, find the determinant and rank of a matrix, partitioned matrices, find the generalized inverse, solution to linear systems, linear, bilinear and quadratic forms and their derivatives, positive definiteness, positice semidefiniteness and nonnegative definiteness of a matrix

Course Precondition

none

Resources

1. Schott, J. R. (2005), Matrix Analysis for Statistics. John Wiley and Sons 2. Harville, D. A. (1997), Matrix Algebra from a Statisticians Perspective. Springer Verlag

Notes

Graybill, F.A. (1983), Matrices with Applications in Statistics. Wadsworth Publishing, Belmont


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Do matrix operations
LO02 Understand the properties of the determinant
LO03 Find the inverse of a matrix
LO04 Do operations with partitioned matrices
LO05 Find the generalized inverse of matrices
LO06 Solve linear systems
LO07 Find the least squares solution of linear systems
LO08 Define linear, bilinear and quadratic forms
LO09 Define positive definite, positive semidefinite and nonnegative definite matrices
LO10 Derive the linear and quadratic forms


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 Probability, Statistics and Mathematics 3
PLO02 Bilgi - Kuramsal, Olgusal Emphasize the importance of Statistics in life 2
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 4
PLO05 Bilgi - Kuramsal, Olgusal Use proper methods and techniques to gather and/or to arrange the data 1
PLO06 Bilgi - Kuramsal, Olgusal Utilize computer systems and softwares
PLO07 Bilgi - Kuramsal, Olgusal Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events 2
PLO08 Bilgi - Kuramsal, Olgusal Apply the statistical analyze methods 2
PLO09 Bilgi - Kuramsal, Olgusal Make statistical inference(estimation, hypothesis tests etc.)
PLO10 Bilgi - Kuramsal, Olgusal Generate solutions for the problems in other disciplines by using statistical techniques 1
PLO11 Bilgi - Kuramsal, Olgusal Discover the visual, database and web programming techniques and posses the ability of writing programme
PLO12 Bilgi - Kuramsal, Olgusal Construct a model and analyze it by using statistical packages
PLO13 Beceriler - Bilişsel, Uygulamalı Distinguish the difference between the statistical methods 1
PLO14 Beceriler - Bilişsel, Uygulamalı Be aware of the interaction between the disciplines related to statistics 2
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Make oral and visual presentation for the results of statistical methods 1
PLO16 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Have capability on effective and productive work in a group and individually 1
PLO17 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
PLO18 Yetkinlikler - Öğrenme Yetkinliği Develop scientific and ethical values in the fields of statistics-and scientific data collection 1


Week Plan

Week Topic Preparation Methods
1 Speical matrices and matrix operations Source reading Öğretim Yöntemleri:
Anlatım
2 Linear independence and rank of matrix Source reading Öğretim Yöntemleri:
Anlatım
3 Determinants and determinant properties Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
4 Finding the inverse of a matrix Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
5 Partitioned matrices Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
6 Elementary transformations, echelon form, equivalent matrices Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
7 Moore Penrose inverse and properties Source reading Öğretim Yöntemleri:
Anlatım
8 Mid-Term Exam Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav
9 Generalized inverse Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
10 Systems of linear equations Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
11 General solution Systems of linear equations Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
12 Least squares solution to systems of linear equations Source reading Öğretim Yöntemleri:
Anlatım, Problem Çözme
13 Linear, bilinear and quadratic forms Source reading Öğretim Yöntemleri:
Anlatım
14 Derivatives of linear and quadratic forms Source reading Öğretim Yöntemleri:
Anlatım
15 Kronecker multiplication Source reading Öğretim Yöntemleri:
Anlatım
16 Term Exams Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav
17 Term Exams Review the topics discussed in the lecture notes and sources 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 7 7
Final Exam 1 18 18
Total Workload (Hour) 109
Total Workload / 25 (h) 4,36
ECTS 4 ECTS

Update Time: 02.05.2023 08:49