ISB501 Matrix Theory

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

Information

Code ISB501
Name Matrix Theory
Term 2022-2023 Academic Year
Term 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. SADULLAH SAKALLIOĞLU
Course Instructor
1


Course Goal / Objective

To provide the students with the necessary information in linear models and multivariate analysis.

Course Content

Basic terms and concepts in the matrix theory, column space, null space, subspace, and Echelon form, type of mxn matrices g-inverse, solution of systems of equations, matrix derivative and properties of positive definit and nnd matrices.

Course Precondition

None

Resources

Franklin A. Graybill (1983), Matrices with Applications in Statistics, Wadsworth International Group, Belmont, California.

Notes

James R. Schott (2005), Matrix Analysis for Statistics, John Wiley and Sons Inc. New Jersey


Course Learning Outcomes

Order Course Learning Outcomes
LO01 Understand the fundamental rules and concepts of matrix
LO02 Define the concepts of linear independence, eigenvalues and eigenvectors
LO03 Learn the concepts of vector space, column space, null space, subspace and reduce to echelon form,
LO04 Gain the findings regarding the inverse of a matrix and know the properties of g inverse
LO05 Have the ability to apply patterned matrices
LO06 Solve the systems of equations and examine the terms of consistency
LO07 Comprehend matrix trace and its properties
LO08 Have the knowedge about matix derivative, and properties of positive definit and n.n.d. matrices


Relation with Program Learning Outcome

Order Type Program Learning Outcomes Level
PLO01 Bilgi - Kuramsal, Olgusal Have in-depth theoretical and practical knowledge about Probability and Statistics
PLO02 Bilgi - Kuramsal, Olgusal They have the knowledge to make doctoral plans in the field of statistics. 3
PLO03 Bilgi - Kuramsal, Olgusal Has comprehensive knowledge about analysis and modeling methods used in statistics. 4
PLO04 Bilgi - Kuramsal, Olgusal Has comprehensive knowledge of methods used in statistics. 3
PLO05 Bilgi - Kuramsal, Olgusal Make scientific research on Mathematics, Probability and Statistics. 3
PLO06 Bilgi - Kuramsal, Olgusal Indicates statistical problems, develops methods to solve. 4
PLO07 Bilgi - Kuramsal, Olgusal Apply innovative methods to analyze statistical problems. 4
PLO08 Bilgi - Kuramsal, Olgusal Designs and applies the problems faced in the field of analytical modeling and experimental researches. 3
PLO09 Bilgi - Kuramsal, Olgusal Access to information and do research about the source. 3
PLO10 Bilgi - Kuramsal, Olgusal Develops solution approaches in complex situations and takes responsibility. 2
PLO11 Bilgi - Kuramsal, Olgusal Has the confidence to take responsibility. 3
PLO12 Beceriler - Bilişsel, Uygulamalı They demonstrate being aware of the new and developing practices.
PLO13 Beceriler - Bilişsel, Uygulamalı He/She constantly renews himself/herself in statistics and related fields. 2
PLO14 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Communicate in Turkish and English verbally and in writing. 3
PLO15 Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği Transmits the processes and results of their studies clearly in written and oral form in national and international environments. 2
PLO16 Yetkinlikler - Öğrenme Yetkinliği It considers the social, scientific and ethical values ​​in the collection, processing, use, interpretation and announcement stages of data and in all professional activities. 3
PLO17 Yetkinlikler - Öğrenme Yetkinliği Uses the hardware and software required for statistical applications.


Week Plan

Week Topic Preparation Methods
1 Notations and definitions ( determinant, rank, trace, qadratic forms, orthogonal martices) Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
2 Similar matrices, Symmetric matrices Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap
3 Eigenvectors and eigenvalues Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap
4 Vector space, vector subspace, basis of a vector space, column and null space of a marrix Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
5 Basic theorems of generalized inverse Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
6 Computing formulas for the g-inverse Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
7 Conditional inverse, Hermite form of matrices Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
8 Mid-Term Exam Review the topics discussed in the lecture notes and references Ölçme Yöntemleri:
Yazılı Sınav
9 solutions to systems of linear equations, Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
10 Approximate solutions to inconsitent systems of linear equations, solutions of least squares Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
11 Pattern matrices Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
12 Trace of matrik and its properties Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
13 Matrix derivatives Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
14 nnd matrices and its properties Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
15 Pd and nnd matrices and its properties Reading the related references Öğretim Yöntemleri:
Anlatım, Soru-Cevap, Tartışma
16 Term Exams Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav, Ödev, Performans Değerlendirmesi
17 Term Exams Review the topics discussed in the lecture notes and sources Ölçme Yöntemleri:
Yazılı Sınav, Ödev, Performans Değerlendirmesi


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

Update Time: 23.11.2022 03:16