COURSE UNIT TITLE

: LINEAR ALGEBRA

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MAT 2026 LINEAR ALGEBRA COMPULSORY 4 0 0 6

Offered By

Statistics

Level of Course Unit

First Cycle Programmes (Bachelor's Degree)

Course Coordinator

PROFESSOR DOCTOR HALIL ORUÇ

Offered to

Statistics
Statistics(Evening)

Course Objective

The course aims at introducing students to the fundamental concepts of linear algebra; ortogonality in Rn, least squares, eigenvalues, ortogonalization, ortogonal, symmetric and pozitive definite matrices and apply them in modern applications.

Learning Outcomes of the Course Unit

1   be able to understand orthogonality in Rn
2   be able to find out least square solutions
3   be able to find the eigenvalues and eigenvectors of a square matrix
4   be able to recognize orthogonal, pozitive definite matrices
5   be able to orthogonally diagonalize symmetric matrices
6   be able to apply concepts of linear algebra to scientific problems

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 The Scalar Product in Rn
2 Orthogonal Subspaces
3 Least Squares Problems
4 Inner Product Spaces
5 Orthonormal Sets
6 The Gram-Schmidt Orthogonalization Process, Orthogonal Polynomials
7 Eigenvalues and Eigenvectors
8 The Characteristic polynomial
9 Problems and discussion
10 Diagonalization
11 Symmetric matrices and diagonalization
12 Positive Definite Matrices and Nonnegative Matrices
13 Scientific Applications; geometry, statistics, computers.
14 Scientific Applications; geometry, statistics, computers.

Recomended or Required Reading

Textbook(s):
Steven J. Leon, Linear Algebra with Applications, 9th edition, Pearson Education, 2015.

Supplementary Book(s): References: D. C. Lay, Linear Algebra and Its Applications, 4th edition, Pearson Education, 2010.
H. Anton, C. Rorres, Elementary Linear Algebra with Applications 11th ed. Wiley 2014.
Materials: Lecture Notes.

Planned Learning Activities and Teaching Methods

Lecture Notes, Presentation, Problem Solving.

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 VZ Vize
2 FN Final
3 BNS BNS VZ * 0.40 + FN * 0.60
4 BUT Bütünleme Notu
5 BBN Bütünleme Sonu Başarı Notu VZ * 0.40 + BUT * 0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Midterm
Quiz
Final Exam

Language of Instruction

English

Course Policies and Rules

Attendance to at least 70% for the lectures is an essential requirement of this course and is the responsibility of the student. It is necessary that attendance to the lecture and homework delivery must be on time. Any unethical behavior that occurs either in presentations or in exams will be dealt with as outlined in school policy. You can find the undergraduate policy at http://web.deu.edu.tr/fen

Contact Details for the Lecturer(s)

Melda Duman
Office: B-211 (Math. Dept.)
Phone: 232-(30)18583
e-mail: melda.duman@deu.edu.tr

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 4 56
Preparations before/after weekly lectures 13 4 52
Preparation for midterm exam 1 18 18
Preparation for quiz etc. 0 0 0
Preparation for final exam 1 20 20
Midterm 1 2 2
Quiz etc. 0 0 0
Final 1 2 2
TOTAL WORKLOAD (hours) 150

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12PO.13PO.14
LO.1543434
LO.2543434
LO.3543434
LO.4543434
LO.5443333
LO.6543545