Course Information
SemesterCourse Unit CodeCourse Unit TitleT+P+LCreditNumber of ECTS Credits
5MATH330Numerical Analysis3+0+035

Course Details
Language of Instruction English
Level of Course Unit Bachelor's Degree
Department / Program Mechatronics Engineering (English)
Mode of Delivery Face to Face
Type of Course Unit Compulsory
Objectives of the Course 1.An introduction to the language, logic, and math of numerical methods as used in engineering and the sciences
2.An opportunity to learn how numerical analyses can be applied to a wide range of problems of importance in the sciences, industry, and society.
Course Content Description of Numerical Methods and application of them particularly in engineering. Error analyses in numerical methods, analitical solutions, numerical methods for the solution of systems (lineer and non linear), approximation methods, interpolation, linear regression, numerical integration.
Course Methods and Techniques
Prerequisites and co-requisities None
Course Coordinator Asist Prof. Haydar Şahin
Name of Lecturers Asist Prof. Uğur DEMİR
Assistants None
Work Placement(s) No

Recommended or Required Reading
Resources James F. Epperson, 2001, An Introduction to Numerical Methods and Analyses,, John Wiley and Sons, ISBN:0471316474.
Yazılım ve Programlama Uygulamalarıyla Mühendisler için Sayısal Yöntemler, Steven C. Chapra Raymond P. Canale, 2002
Applied Numerical Methods with MATLAB for Engineers and Scientists, Published by McGraw-Hill Education, Steven C. Chapra, 2018
Applied Numerical Methods with MATLAB for Engineers and Scientists, Published by McGraw-Hill Education, Steven C. Chapra, 2018
1 adet yıliçi sınavı, 1 adet final

Course Category
Mathematics and Basic Sciences %40
Engineering %30
Science %30

Planned Learning Activities and Teaching Methods
Activities are given in detail in the section of "Assessment Methods and Criteria" and "Workload Calculation"

Assessment Methods and Criteria
In-Term Studies Quantity Percentage
Mid-terms 1 % 20
Assignment 1 % 20
Final examination 1 % 60
Total
3
% 100

 
ECTS Allocated Based on Student Workload
Activities Quantity Duration Total Work Load
Course Duration 14 3 42
Hours for off-the-c.r.stud 14 4 56
Assignments 14 1 14
Mid-terms 1 2 2
Laboratory 14 2 28
Final examination 1 2 2
Total Work Load   Number of ECTS Credits 5 144

Course Learning Outcomes: Upon the successful completion of this course, students will be able to:
NoLearning Outcomes
1 Learning how mathematical models can be formulated on the basis of scientific principles to simulate the behavior of a simple physical system.
2 Understanding how numerical methods afford a means to generate solutions in a manner that can be implemented on a digital computer.
3 Understanding the different types of conservation laws that lie beneath the models used in the various engineering disciplines and appreciating the difference between steady-state and dynamic solutions of these models.
4 Learning about the different types of numerical methods
5 Learn the calculation mode and numerical variables of the MATLAB program.
6 Learning how to create well-documented M-files and function files
7 Understanding the distinction between accuracy and precision.
8 Learning types of errors and how to quantify error: Roundoff and Truncation.
9 Knowing how to solve a roots problem with different methods
10 Knowing how to use MATLAB's functions to estimate roots
11 Recognizing the difference between bracketing and open methods for root location.
12 Knowing how to evaluate polynomial coefficients and interpolate with MATLAB’s functions.


Weekly Detailed Course Contents
WeekTopicsStudy MaterialsMaterials
1 Introduction, Error in numerical analysis
2 Error analysis of functions, least square concepts in numerical methods
3 Solution of linear equations systems, Direct methods, Cramer Method, Gauss Elimination
4 Gauss Jordan, LU method
5 Doolittle Methods Cholesky Method
6 Jacobi Iterative Method
7 Gauss Siedel Iterative Method, Error Analysis of linear equations systems
8 Midterm exam
9 Non linear equation systems, Root finding
10 Bisection Method
11 Regula Falsi, Succesive Substitution Method
12 Approximation methods, Interpolation, Linear Regression, Interpolation Polynoms
13 Lagrange interpolation, Newton Interpolation
14 Numerical integration, pivot point, interpolation, short presentations
15 Gaussian Quadrature and Gauss Legendre Integration formulations, extrapolation, short presentations
16 Final exam


Contribution of Learning Outcomes to Programme Outcomes
P1 P2 P3 P4 P5 P6 P7 P8 P9 P10 P11 P12
All 5 5 5
C1 5 5 5
C2 5 5 5
C3 5 5 5
C4 5 5 5
C5 5 5 5
C6 5 5 5
C7 5 5 5
C8 5 5 5
C9 5 5 5
C10 5 5 5
C11 5 5 5
C12 5 5 5

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https://obs.gedik.edu.tr/oibs/bologna/progCourseDetails.aspx?curCourse=207065&curProgID=5596&lang=en