FACULTY OF ARTS AND SCIENCES

Department of Mathematics

MATH 226 | Course Introduction and Application Information

Course Name
Linear Algebra II
Code
Semester
Theory
(hour/week)
Application/Lab
(hour/week)
Local Credits
ECTS
MATH 226
Spring
3
0
3
5

Prerequisites
  MATH 225 To get a grade of at least FD
Course Language
English
Course Type
Required
Course Level
First Cycle
Mode of Delivery face to face
Teaching Methods and Techniques of the Course Problem Solving
Q&A
Lecture / Presentation
Course Coordinator -
Course Lecturer(s)
Assistant(s)
Course Objectives This course aims to teach students to define vector spaces, eigenvalues and eigenvectors, orthogonality and give the applications of them in various fields.
Learning Outcomes The students who succeeded in this course;
  • define vector spaces and subspaces.
  • find bases and dimensions of vector spaces.
  • employ rank of a matrix.
  • find eigenvalues and related eigenvectors.
  • employ diagonalization.
  • solve application problems.
  • analyze ortogonallity, ortogonal and orthonormal sets.
  • use Gram-Schmidt process to obtain an orthogonal set.
Course Description In this course, the concepts of bases, dimensions, linear transformations, orthogonality, inner product spaces, eigenvalues, eigenvectors and diagonalization are discussed.

 



Course Category

Core Courses
X
Major Area Courses
Supportive Courses
Media and Management Skills Courses
Transferable Skill Courses

 

WEEKLY SUBJECTS AND RELATED PREPARATION STUDIES

Week Subjects Related Preparation
1 Vector spaces and subspaces David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 4.1
2 Null spaces, column spaces and linear transformations, Linearly independent sets, bases David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 4.2, 4.3
3 Linearly independent sets, bases coordinate systems David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 4.3, 4.4
4 The dimension of a vector space, rank David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 4.5, 4.6
5 Change of bases, application to difference equations David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 4.7, 4.8
6 Application to Markov chains David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 4.9
7 Midterm Exam
8 Eigenvalues and eigenvectors, the characteristic equation David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 5.1, 5.2
9 Diagonalization, eigenvectors and linear transformations David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 5.3, 5.4
10 Eigenvectors and linear transformations, complex eigenvalues David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 5.4, 5.5
11 Complex eigenvalues, discrete dynamical systems David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 5.5, 5.6
12 Application to differential equations David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 5.7
13 Inner product, length and orthogonality, orthogonal sets David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 6.1, 6.2.
14 Orthogonal projections, the Gram-Schmidt process David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications" by Pearson, Global Edition,2015. ISBN-13:978-0321982384 Section 6.3, 6.4.
15 Semester review
16 Final Exam

 

Course Notes/Textbooks

 David C.Lay, Stephan R.Lay and Judi J. McDonald, "Linear Algebra and Its Applications", Pearson, Global Edition,2015. ISBN-13:978-0321982384

Suggested Readings/Materials

 

EVALUATION SYSTEM

Semester Activities Number Weigthing
Participation
Laboratory / Application
Field Work
Quizzes / Studio Critiques
5
25
Portfolio
Homework / Assignments
Presentation / Jury
Project
Seminar / Workshop
Oral Exams
Midterm
1
25
Final Exam
1
50
Total

Weighting of Semester Activities on the Final Grade
6
50
Weighting of End-of-Semester Activities on the Final Grade
1
50
Total

ECTS / WORKLOAD TABLE

Semester Activities Number Duration (Hours) Workload
Theoretical Course Hours
(Including exam week: 16 x total hours)
16
3
48
Laboratory / Application Hours
(Including exam week: '.16.' x total hours)
16
0
Study Hours Out of Class
14
3
42
Field Work
0
Quizzes / Studio Critiques
5
2
10
Portfolio
0
Homework / Assignments
0
Presentation / Jury
0
Project
0
Seminar / Workshop
0
Oral Exam
0
Midterms
1
20
20
Final Exam
1
30
30
    Total
150

 

COURSE LEARNING OUTCOMES AND PROGRAM QUALIFICATIONS RELATIONSHIP

#
Program Competencies/Outcomes
* Contribution Level
1
2
3
4
5
1

To be able to have a grasp of basic mathematics, applied mathematics or theories and applications of statistics.

X
2

To be able to use advanced theoretical and applied knowledge, interpret and evaluate data, define and analyze problems, develop solutions based on research and proofs by using acquired advanced knowledge and skills within the fields of mathematics or statistics.

3

To be able to apply mathematics or statistics in real life phenomena with interdisciplinary approach and discover their potentials.

4

To be able to evaluate the knowledge and skills acquired at an advanced level in the field with a critical approach and develop positive attitude towards lifelong learning.

X
5

To be able to share the ideas and solution proposals to problems on issues in the field with professionals, non-professionals.

X
6

To be able to take responsibility both as a team member or individual in order to solve unexpected complex problems faced within the implementations in the field, planning and managing activities towards the development of subordinates in the framework of a project.

7

To be able to use informatics and communication technologies with at least a minimum level of European Computer Driving License Advanced Level software knowledge.

8

To be able to act in accordance with social, scientific, cultural and ethical values on the stages of gathering, implementation and release of the results of data related to the field.

9

To be able to possess sufficient consciousness about the issues of universality of social rights, social justice, quality, cultural values and also environmental protection, worker's health and security.

10

To be able to connect concrete events and transfer solutions, collect data, analyze and interpret results using scientific methods and having a way of abstract thinking.

X
11

To be able to collect data in the areas of Mathematics or Statistics and communicate with colleagues in a foreign language.

12

To be able to speak a second foreign language at a medium level of fluency efficiently.

13

To be able to relate the knowledge accumulated throughout the human history to their field of expertise.

*1 Lowest, 2 Low, 3 Average, 4 High, 5 Highest

 


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