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| IST2006 | Numerical Analysis | 4+0+0 | ECTS:5 | | Year / Semester | Spring Semester | | Level of Course | First Cycle | | Status | Compulsory | | Department | DEPARTMENT of STATISTICS and COMPUTER SCIENCES | | Prerequisites and co-requisites | None | | Mode of Delivery | Face to face, Practical | | Contact Hours | 14 weeks - 4 hours of lectures per week | | Lecturer | Prof. Dr. Orhan KESEMEN | | Co-Lecturer | PROF. DR. Türkan ERBAY DALKILIÇ | | Language of instruction | Turkish | | Professional practise ( internship ) | None | | | | The aim of the course: | | The aim of this course is to improve the ability to produce simple solutions to intentional programming and complex problems.. |
| Learning Outcomes | CTPO | TOA | | Upon successful completion of the course, the students will be able to : | | | | LO - 1 : | summarise the basic knowledge and kinds of error | 1,2,3,4 | 1,3 | | LO - 2 : | describe the root of the linear equation using the numerical methods | 1,2,3,4 | 1,3 | | LO - 3 : | describe the solutions of the linear and non-linear simultaneous equations using numerical methods | 1,2,3,4 | 1,3 | | LO - 4 : | use linear interpolation and quadratic interpolation methods to find the empirical function | 1,2,3,4 | 1,3 | | LO - 5 : | determine the integration of a function via using Simpson and Ronberg methods | 1,2,3,4 | 1,3 | | LO - 6 : | obtain the simple linear regression model with numerical approach methods | 1,2,3,4 | 1,3 | | CTPO : Contribution to programme outcomes, TOA :Type of assessment (1: written exam, 2: Oral exam, 3: Homework assignment, 4: Laboratory exercise/exam, 5: Seminar / presentation, 6: Term paper), LO : Learning Outcome | | |
| Numerical calculation, finding roots of equation and polynomial, solving non-linear equation systems, matrix algebra, solving linear equation systems, linear regression equation, linear curve fitting, non-linear curve fitting, interpolation, Fourier series, numerical differential and integral. |
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| Course Syllabus | | Week | Subject | Related Notes / Files | | Week 1 | Basic concepts in numerical analysis and mathematical snippets. | | | Week 2 | Errors in numerical solutions and sources of errors. | | | Week 3 | Numerical methods for nonlinear equations: Iteration method. | | | Week 4 | Halfway methods for the f(x)=0: Bisection method, Regula False method, Newton Raphson method. | | | Week 5 | Numerical methods for nonlinear equations: A simple iteration, Newton Raphson method. | | | Week 6 | Interpolation | | | Week 7 | Newton Interpolation | | | Week 8 | Approach methods: Approach to discrete data | | | Week 9 | Mid-term exam
| | | Week 10 | Approach methods: Approach to continuous functions | | | Week 11 | Numerical methods for systems of linear algebraic equations: Gauss elimination method | | | Week 12 | Numerical methods for systems of linear algebraic equations: Gauss jordan reduction method, LU decomposition method. | | | Week 13 | Numerical methods for systems of linear algebraic equations: A simple iteration, Gauss Seidel iteration. | | | Week 14 | Numerical integration methods: Yrapezoidal method, Simpson Method. | | | Week 15 | Numerical integration methods: Romberg approach. | | | Week 16 | End-of-term exam | | | |
| 1 | Tapramaz, R. 2002; Sayısal Çözümleme, Literatür Yayıncılık, İstanbul. | | | |
| 1 | Karagöz, İ., 2007; Sayısal analiz ve mühendislik uygulamaları,Nobel yayınları, No:1281, Bursa. | | | |
| Method of Assessment | | Type of assessment | Week No | Date | Duration (hours) | Weight (%) | | Mid-term exam | 9 | 26/11/2021 | 2 | 50 | | End-of-term exam | 16 | 17/01/2022 | 2 | 50 | | |
| Student Work Load and its Distribution | | Type of work | Duration (hours pw) | No of weeks / Number of activity | Hours in total per term | | Yüz yüze eğitim | 4 | 14 | 56 | | Sınıf dışı çalışma | 3 | 14 | 42 | | Arasınav için hazırlık | 8 | 1 | 8 | | Arasınav | 1.5 | 1 | 1.5 | | Dönem sonu sınavı için hazırlık | 15 | 1 | 15 | | Dönem sonu sınavı | 1.5 | 1 | 1.5 | | Total work load | | | 124 |
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