Information Systems Engineering
Bachelor	TR-NQF-HE: Level 6	QF-EHEA: First Cycle	EQF-LLL: Level 6

Ders Genel Tanıtım Bilgileri

Course Code:

EFC202

Ders İsmi:

Numerical Analysis

Ders Yarıyılı:

Spring

Ders Kredileri:

Theoretical	Practical	Laboratory	ECTS
3	1	0	7

Language of instruction:

Turkish

Ders Koşulu:

Ders İş Deneyimini Gerektiriyor mu?:

Yes

Type of course:

Required

Course Level:

Bachelor

TR-NQF-HE:6. Master`s Degree

QF-EHEA:First Cycle

EQF-LLL:6. Master`s Degree

Mode of Delivery:

Face to face

Course Coordinator :

Asst. Prof. Dr. SEDA YAMAÇ AKBIYIK

Course Lecturer(s):

Asst. Prof. Dr. TOLGA KUDRET KARACA
Asst. Prof. Dr. KÜBRA EROĞLU
Asst. Prof. Dr. SEDA YAMAÇ AKBIYIK

Course Assistants:

Dersin Amaç ve İçeriği

Course Objectives:	To learn Numerical Analysis techniques, which are necessary for engineers in solving advanced engineering mathematical problems that do not have analytical solutions, especially in computer programming logic.
Course Content:	Concept of Error and Error Analysis, Open and Closed methods to approximately find the root of the equation. Solution methods of systems of linear equations. Nonlinear systems of equations solution methods. Curve fitting, interpolation and extrapolation methods. Numerical derivative methods. Numerical integration calculation methods.

Learning Outcomes

The students who have succeeded in this course;

Learning Outcomes

1 - Knowledge
Theoretical - Conceptual
2 - Skills
Cognitive - Practical
1) To be able to apply appropriate methods for the solution of engineering problems with matrix equations.
2) Ability to detect errors in the approximate solution found.
3) To be able to apply different interpolation and curve fitting methods to engineering problems.
4) To be able to apply numerical differentiation and integration methods to various problems.
5) To be able to solve linear and non-linear equations and systems of equations with various methods.
3 - Competences
Communication and Social Competence
Learning Competence
Field Specific Competence
Competence to Work Independently and Take Responsibility

Ders Akış Planı

Week	Subject	Related Preparation
1)	Introduction to Numerical Analysis, Concept of Error, Truncation Error and Machine Numbers, Error Analysis, Errors in Arithmetic Operations	Lecture Notes
2)	Numerical Methods to Find the Approximate Root of the Equation, Bisection Method, Regula-False Method, Secant Method	Lecture Notes
3)	Newton-Raphson Method, Fixed Point Concept, Fixed Point Iteration Method	Lecture Notes
4)	Linear Equation Systems and Their Solution Methods: Gauss Elimination Method, Gauss-Jordan Method, Cramer Method, Multiplication Method with the Inverse of the Coefficients Matrix	Lecture Notes
5)	Solution Methods of Systems of Linear Equations: LU Decomposition Method, Doolitle Method, Crout Method, Cholesky Method	Lecture Notes
6)	Iterative Methods, Convergence of Iterative Methods, Jacobi Method, Gauss-Siedel Method	Lecture Notes
7)	Nonlinear Equation Systems and Solutions: Simple Iteration Method, Newton Method	Lecture Notes
8)	Midterm	Lecture Notes
9)	Interpolation (Curve Fitting)	Lecture Notes
10)	Lagrange Polynomials and Lagrange Interpolation	Lecture Notes
11)	Divided Differences (Newton) Interpolation, Least Squares Method	Lecture Notes
12)	Numerical Derivative Concept and Numerical Derivative Calculation Methods	Lecture Notes
13)	Numerical Integral Concept and Numerical Integral Calculation Methods	Lecture Notes
14)	Trapezoidal Rule, Simpson's Rule, Open Newton-Cotes Formulas, Composite Trapezoidal Rule, Composite Simpson's Rule	Lecture Notes
15)	Final Exam	Lecture Notes

Sources

Course Notes / Textbooks:	Numerical Analysis, Richard L. Burden (Author), J. Douglas Faires (Author), Annette M. Burden (Author), Pearson. Sayısal Çözüm, Steven C. Chapra, Raymond P. Canale (Çev. H. Heperkan ve U. Kesgin),“Yazılım ve Programlama Uygulamalarıyla Mühendisler İçin Sayısal Yöntemler”, Literatür Yayıncılık.
References:	Uğur Arifoğlu, "Matlab 9.8 ve Sayısal Uygulamaları", Alfa Yayıncılık, 2020.

Ders - Program Öğrenme Kazanım İlişkisi

Ders Öğrenme Kazanımları	1	2	3	4	5
Program Outcomes

Ders - Öğrenme Kazanımı İlişkisi

No Effect	1 Lowest	2 Low	3 Average	4 High	5 Highest

Program Outcomes

Level of Contribution

Assessment & Grading

Semester Requirements	Number of Activities	Level of Contribution
Midterms	1	% 50
Final	1	% 50
total		% 100
PERCENTAGE OF SEMESTER WORK		% 50
PERCENTAGE OF FINAL WORK		% 50
total		% 100