Ordu University Lifelong Learning Programme

Description of Individual Course Units

Course Unit Code	Course Unit Title	Type of Course Unit	Year of Study	Semester	Number of ECTS Credits
MAT30620121310	NUMERICAL ANALYSIS INTRODUCTION	Compulsory	3	6	5

Level of Course Unit

First Cycle

Objectives of the Course

To find suitable methods which have best approach and to extract meaningful and useful results from them in order to solve mathematical problems.

Name of Lecturer(s)

Yrd. Doç. Dr.Mehmet Korkmaz

Learning Outcomes

1	To determine: What numerical analysis is. Definition, purpose and features of numerical analysis. Error analysis: Error sources, Error types.
2	To solve linear algebraic equations with numerical methods
3	To calculate solutions of nonlinear equations with numerical methods
4	To investigate eigenvalue problems in matrix

Mode of Delivery

Formal Education

Prerequisites and co-requisities

None

Recommended Optional Programme Components

None

Course Contents

What is numerical analysis? Definition, purpose and features of numerical analysis. Error analysis: Error sources, Error types. Numerical solutions of nonlinear equations: Halving method, Simple iteration method, Newton-Raphson method, Regula-False method, Secant method. Numerical solutions of systems of nonlinear equations: Newtons's method, Simple iteration method. Numerical solutions of systems of linear equations: Gaussian elimination, LU-factorization, Gauss-Jourdan method, Least squares method, Gauss Seidel method, Jacobi method. Eigenvalue problems in matrix: One of the largest and smallest eigenvalues of the matrix, Force method, inverse power method.

Weekly Detailed Course Contents

Week	Theoretical	Practice	Laboratory
1	What is numerical analysis? Definition, purpose and features of numerical analysis. Error analysis: Error sources, Error types.
2	Numerical solutions of nonlinear equations: Simple iteration method
3	Newton-Raphson method
4	Regula-False method
5	Secant method, halving method
6	Numerical solutions of systems of nonlinear equations: Simple iteration method
7	Newton method
8	Midterm exam
9	Numerical solutions of systems of linear equations
10	Gaussian elimination, Gauss-Jourdan method
11	LU-factorization
12	Jacobi method, Gauss Seidel method,
13	Eigenvalue problem
14	One of the largest and smallest eigenvalues of the matrix
15	Force method, inverse power method
16	final exam

Recommended or Required Reading

Planned Learning Activities and Teaching Methods

Assessment Methods and Criteria

Term (or Year) Learning Activities	Quantity	Weight
SUM		0
End Of Term (or Year) Learning Activities	Quantity	Weight
SUM		0
Yarıyıl (Yıl) İçi Etkinlikleri		40
Yarıyıl (Yıl) Sonu Etkinlikleri		60
SUM		100

Language of Instruction

Turkish

Work Placement(s)

None

Workload Calculation

Activities	Number	Time (hours)	Total Work Load (hours)
Midterm Examination	1	2	2
Final Examination	1	2	2
Makeup Examination	1	2	2
Attending Lectures	14	4	56
Problem Solving	5	3	15
Self Study	14	1	14
Individual Study for Homework Problems	5	3	15
Individual Study for Mid term Examination	8	3	24
Individual Study for Final Examination	8	3	24
TOTAL WORKLOAD (hours)			154

Contribution of Learning Outcomes to Programme Outcomes

	PO 1	PO 2	PO 3	PO 4	PO 5	PO 6	PO 7
LO1	4
LO2	4
LO3	4
LO4	4

* Contribution Level : 1 Very low 2 Low 3 Medium 4 High 5 Very High