TEXTILE AND FASHION DESIGN | |||||
Bachelor | TR-NQF-HE: Level 6 | QF-EHEA: First Cycle | EQF-LLL: Level 6 |
Course Code | Course Name | Semester | Theoretical | Practical | Credit | ECTS |
MATH3012 | Numerical Analysis | Spring | 2 | 2 | 3 | 6 |
This catalog is for information purposes. Course status is determined by the relevant department at the beginning of semester. |
Language of instruction: | English |
Type of course: | Non-Departmental Elective |
Course Level: | Bachelor’s Degree (First Cycle) |
Mode of Delivery: | Face to face |
Course Coordinator : | |
Recommended Optional Program Components: | None |
Course Objectives: | Numerical Analysis is concerned with the mathematical derivation, description and analysis of obtaining numerical solutions of mathematical problems. We have several objectives for the students. Students should obtain an intuitive and working understanding of some numerical methods for the basic problems of numerical analysis. They should gain some appreciation of the concept of error and of the need to analyze and predict it. And also they should develop some experience in the implementation of numerical methods by using a computer. |
The students who have succeeded in this course; The students who succeeded in this course; o will be able to define Errors, Big O Notation, Stability and Condition Number, Taylor’s Theorem. o will be able to solve Nonlinear Equations. o will be able to solve Linear Systems. o will be able to use Iterative Methods for Linear Systems. o will be able to calculate Eigenvalues and Eigenvectors. o will be able to solve System of Nonlinear Equations. o will be able to calculate Interpolating and Polynomial Approximation. |
In this course the solution of linear and nonlinear systems will be discussed numerically. Also iterative methods for linear systems will be taught. |
Week | Subject | Related Preparation |
1) | Errors, Big O Notation, Stability and Condition Number, Taylor’s Theorem. | |
2) | The Solution of Nonlinear Equations in the form of f(x)=0: Bisection Method, Fixed Point Iteration. | |
3) | Newton-Rapson Method, Secant Method. | |
4) | The Solution of Linear System : Solving Triangular System, Gauss Elimination and Pivoting. | |
5) | LU Factorization, Tridiagonal System, Vector and Matrix Norms | |
6) | Sensitivity of Linear Equations. Condition Number and Stability. | |
7) | Iterative Methods for Linear Systems: Jacobi Method. | |
8) | Gauss Seidel Method. Diagonally Dominant Matrix. Errors in Solving Linear Systems. | |
9) | Eigenvalues and Eigenvectors: The Power Method. The Inverse Power Method. | |
10) | System of Nonlinear Equations: Newton’s Method. | |
11) | Interpolating and Polynomial Approximation: Lagrange interpolation polynomial, Newton Interpolation. | |
12) | Piecewise Linear Interpolation, Cubic Spline. | |
13) | Least Square Approximation: Curve Fitting. | |
14) | Inconsistent System of Equations. Errors in Interpolation . |
Course Notes / Textbooks: | Numerical Methods Using MATLAB (Fourth Edition), John H. Mathews and Kurtis D. Fink, Pearson Prentice Hall |
References: |
Semester Requirements | Number of Activities | Level of Contribution |
Attendance | 16 | % 0 |
Laboratory | 16 | % 5 |
Quizzes | 5 | % 10 |
Midterms | 2 | % 45 |
Final | 1 | % 45 |
Total | % 105 | |
PERCENTAGE OF SEMESTER WORK | % 60 | |
PERCENTAGE OF FINAL WORK | % 45 | |
Total | % 105 |
Activities | Number of Activities | Duration (Hours) | Workload |
Course Hours | 16 | 3 | 48 |
Laboratory | 14 | 1 | 14 |
Study Hours Out of Class | 16 | 2 | 32 |
Quizzes | 3 | 5 | 15 |
Midterms | 2 | 5 | 10 |
Final | 1 | 5 | 5 |
Total Workload | 124 |
No Effect | 1 Lowest | 2 Low | 3 Average | 4 High | 5 Highest |
Program Outcomes | Level of Contribution |