| TYPE OF COURSE UNIT | Elective Course |
| LEVEL OF COURSE UNIT | Master's Degree With Thesis |
| YEAR OF STUDY | - |
| SEMESTER | - |
| NUMBER OF ECTS CREDITS ALLOCATED | 10 |
| NAME OF LECTURER(S) | Professor Nizami Gasilov
Assistant Professor Elmas Burcu Mamak Ekinci
|
| LEARNING OUTCOMES OF THE COURSE UNIT |
At the end of this course, the students;
1) They learn the basic concepts and techniques of numerical analysis.
2) They can evaluate possible calculation errors.
3) Learns numerical methods developed for solving mathematical problems.
4) Solve engineering problems by designing effective algorithms for computer systems.
|
| MODE OF DELIVERY | Face to face |
| PRE-REQUISITES OF THE COURSE | No |
| RECOMMENDED OPTIONAL PROGRAMME COMPONENT | None |
| COURSE DEFINITION | Summary of some topics of mathematical analysis. Taylor's theorem. Error analysis. Error propagation. Numerical solution methods of nonlinear algebraic equations. Numerical solution methods of linear equation systems. Gaussian elimination method. Iterative Newton's method for solving nonlinear systems of equations. Interpolation and approximation with Polynomials. Lagrange and Newton polynomials. Curve fitting using the least squares method. Numerical differentiation and integration. |
| COURSE CONTENTS | | WEEK | TOPICS |
|---|
| 1st Week | Course introduction, review of some topics from calculus and introduction to numerical analysis | | 2nd Week | Installing the R program, introduction to the program and basic operations. | | 3rd Week | Error analysis, taylor series. | | 4th Week | Solving Nonlinear equations (Bracketing Methods, open methods) | | 5th Week | Solving Nonlinear equations (Newton Raphson method) | | 6th Week | Solving a System of Linear Equations (The graphical method, Cramer's rule) | | 7th Week | Solving a System of Linear Equations (Gauss elimination method) | | 8th Week | Midterm exam | | 9th Week | Curve fitting | | 10th Week | Least Square Regression | | 11th Week | Interpolation | | 12th Week | Lagrange Interpolation | | 13th Week | Numerical Differentiation and Integration | | 14th Week | Review |
|
| RECOMENDED OR REQUIRED READING | 1. Chapra, Steven C., Canale Raymond P. (2017). Yazılım ve Programlama Uygulamalarıyla Mühendisler için Sayısal Yöntemler (4. Basımdan çeviri). Literatür Yayıncılık.
2. Bloomfield, V.A. (2014). Usign R for Numerical Analysis in Science and Engineering. A Chapman & Hall Book.
3. Howard, J.P, (2017) Computational Methods for Numerical Analysis with R. A Chapman & Hall Book.
4. Kincaid, D., Cheney, W. (2012). Nümerik Analiz-Bilimsel Hesaplama Matematiği (Üçüncü Baskıdan Çeviri). Gazi Kitabevi.
5. Tezer Sezgin, M., Bozkaya C. (2018). Numerical Analysis. ODTÜ Basım İşbirliği. |
| PLANNED LEARNING ACTIVITIES AND TEACHING METHODS | Lecture,Questions/Answers,Practice,Problem Solving |
| ASSESSMENT METHODS AND CRITERIA | | | Quantity | Percentage(%) |
|---|
| Mid-term | 1 | 35 | | Assignment | 2 | 10 | | Project | 1 | 15 | | Total(%) | | 60 | | Contribution of In-term Studies to Overall Grade(%) | | 60 | | Contribution of Final Examination to Overall Grade(%) | | 40 | | Total(%) | | 100 |
|
| ECTS WORKLOAD |
| Activities |
Number |
Hours |
Workload |
| Midterm exam | 1 | 2 | 2 | | Preparation for Quiz | | | | | Individual or group work | | | | | Preparation for Final exam | 1 | 70 | 70 | | Course hours | 14 | 3 | 42 | | Preparation for Midterm exam | 1 | 50 | 50 | | Laboratory (including preparation) | | | | | Final exam | 1 | 2 | 2 | | Homework | 2 | 20 | 40 | | Presentation (including preperation) | 1 | 40 | 40 | | Project | 1 | 45 | 45 | | Total Workload | | | 291 |
|---|
| Total Workload / 30 | | | 9,7 |
|---|
| ECTS Credits of the Course | | | 10 |
|---|
|
| LANGUAGE OF INSTRUCTION | Turkish |
| WORK PLACEMENT(S) | No |
| | |
