Undergraduate
Faculty of Science and Letters
Mathematics And Computer Science
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Numerical Methods

Course CodeSemester Course Name LE/RC/LA Course Type Language of Instruction ECTS
MBT1008 1 Numerical Methods 4/0/0 BSC Turkish 6
Course Goals
 This course introduces basic methods, algorithms and programming techniques to solve mathematical problems. The course is designed for students to learn how to develop numerical methods and estimate numerical errors using basic calculus concepts and results.
Prerequisite(s) None
Corequisite(s) None
Special Requisite(s) None
Instructor(s) Assist. Prof. Dr. Günay Aslan, Assist. Prof. Dr. Uğur Gönüllü
Course Assistant(s) None
Schedule Wednesday 11:00-13:00 Wednesday 13:00-15:00
Office Hour(s) 3A-15, Tuesday 10:00-11:00
Teaching Methods and Techniques -Lectures and recitation.
Principle Sources -Richard L. Burden and J. Douglas Faires Numerical Analysis, ninth edition, Brooks/Cole, Cengage Learning 2011, ISBN-13:978-0-538-73564-3.
Other Sources -K. Atkinson and W. Han, Elementary Numerical Analysis, John Wiley, 3rd edition.

-Cheney,W.,-Kincaid,D., Numerical Mathematics and Computing,Brooks,1985 
Course Schedules
Week Contents Learning Methods
1. Week Review of Calculus, Taylor Polynomial Lectures and recitation
2. Week Round-off Errors, Computer Arithmetic and Rate of Convergence Lectures and recitation
3. Week The Bisection Method, Fixed-Point Iteration Lectures and recitation
4. Week Newton’s Method, Secant Method Lectures and recitation
5. Week False Position Method, Interpolation Lectures and recitation
6. Week Lagrange Interpolating Polynomial, Neville’s Method Lectures and recitation
7. Week Inverse Interpolation, Divided Differences Lectures and recitation
8. Week Forward-Backward Differences Lectures and recitation
9. Week Centered Differences Lectures and recitation
10. Week Numerical Differentiation, Richardson Extrapolation Lectures and recitation
11. Week Numerical Integration, Open-Closed Newton-Cotes Formulas Lectures and recitation
12. Week Composite Numerical Integration, Error Analysis Lectures and recitation
13. Week Romberg Integration, Elementary Theory of Initial-Value Problems Euler’s Method Lectures and recitation
14. Week Modified Euler, Heun and Runge-Kutta of Order 4 Methods Lectures and recitation
15. Week Final week Exams
16. Week Final week Exams
17. Week Final week Exams
Assessments
Evaluation tools Quantity Weight(%)
Homework / Term Projects / Presentations 1 50
Final Exam 1 50


Program Outcomes
PO-1Interpreting advanced theoretical and applied knowledge in Mathematics and Computer Science.
PO-2Critiquing and evaluating data by implementing the acquired knowledge and skills in Mathematics and Computer Science.
PO-3Recognizing, describing, and analyzing problems in Mathematics and Computer Science; producing solution proposals based on research and evidence.
PO-4Understanding the operating logic of computer and recognizing computational-based thinking using mathematics as a discipline.
PO-5Collaborating as a team-member, as well as individually, to produce solutions to problems in Mathematics and Computer Science.
PO-6Communicating in a foreign language, and interpreting oral and written communicational abilities in Turkish.
PO-7Using time effectively in inventing solutions by implementing analytical thinking.
PO-8Understanding professional ethics and responsibilities.
PO-9Having the ability to behave independently, to take initiative, and to be creative.
PO-10Understanding the importance of lifelong learning and developing professional skills continuously.
PO-11Using professional knowledge for the benefit of the society.
Learning Outcomes
LO-1Understand IEEE standard binary floating point format, machine precision and computer errors
LO-2Develop understanding of the Talyor series to set up approximate polynomials.
LO-3Use the bisection method to solve the equation f(x)=0 and estimate the number of iterations in the algorithm to achieve desired accuracy with the given tolerance
LO-4Use the iterative method to find the fixed point of the function f(x), and analyze the error of the algorithm after n steps.
LO-5Use Newton's method or the Secant method to solve the equation f(x)=0 within the given tolerance.
LO-6Use polynomial interpolations, including the Lagrange polynomial for curve fitting, or data analysis; use Neville's iterative algorithm, Newton's divided difference algorithms to evaluate the interpolations.
LO-7Derive difference formulas to approximate derivatives of functions and use the Lagrange polynomial to estimate the errors of the approximations.
LO-8Use the open or closed Newton-Cotes formula, including the Trapezoidal rule and Simpson's rule, to approximate definite integrals; use the Lagrange polynomial to estimate the degree of accuracy; derive the composite numerical integration using the open or closed Newton-Cotes formula.
LO-9Calculate improper integrals in numerical ways.
Course Assessment Matrix:
Program Outcomes - Learning Outcomes Matrix
 PO 1PO 2PO 3PO 4PO 5PO 6PO 7PO 8PO 9PO 10PO 11