Course Information

Course Title	Code	Semester	L+U Hour	Credits	ECTS
NUMERICAL ANALYSIS	YMH222	4. Semester	2 + 2	3.0	4.0

Prerequisites

None

Language of Instruction	Turkish
Course Level	Bachelor's Degree
Course Type	Compulsory
Mode of delivery
Course Coordinator
Instructors
Assistants
Goals	Aim of this course is to teach the students understanding and analysing of mathematical theory of numerical problems encountered in their profession, making error analysis, and improving the ability of computer programming.
Course Content	Order of Convergence, Difference Equations, Computer arithmetic and error analysis, Solutions of nonlinear equations, Fixed point and iterative techniques, Numerical derivative, Numerical integration
Learning Outcomes	1) Understanding programming 2) Taylor series and error analysis 3) Choosing algorithms for nonlinear equations 4) Taking derivative in computer 5) Extrapolation 6) Choosing algorithms for integral 7) Creating algorithms and programming

Week	Topics	Teaching and Learning Methods and Techniques	Study Materials
1. Week	Introduction to Numerical Analysis	Lecture	Presentation (Including Preparation Time)
2. Week	Taylor series and error analysis	Lecture	Presentation (Including Preparation Time)
3. Week	Difference equations	Lecture	Presentation (Including Preparation Time)
4. Week	Computer arithmetic	Lecture	Presentation (Including Preparation Time)
5. Week	Locating roots of equations; bisection method	Lecture	Presentation (Including Preparation Time)
6. Week	Newton method, Secant method	Lecture	Presentation (Including Preparation Time)
7. Week	Fixed point, Polynomial interpolation	Lecture	Presentation (Including Preparation Time)
8. Week	Divided difference	Lecture	Presentation (Including Preparation Time)
9. Week	Midterm Exam	Lecture	Presentation (Including Preparation Time)
10. Week	Hermite interpolation	Lecture	Presentation (Including Preparation Time)
11. Week	Numerical diferentiation and Richardson extrapolation	Lecture	Presentation (Including Preparation Time)
12. Week	Numerical integration; trapezoid rule	Lecture	Presentation (Including Preparation Time)
13. Week	Gauss quadrature formula	Lecture	Presentation (Including Preparation Time)
14. Week	Romberg algorithm	Lecture	Presentation (Including Preparation Time)

Recommended Sources

Cheney,W.,-Kincaid,D., Numerical Analysis Mathematics of Scientific Computing,AMS,2009

Mathews. J.H., Numerical Methods for Mathematics, Science and Engineering, 2nd Ed, 1992

Yakowitz,S., An Introduction to Numerical Computations, Macmillan, 1989

*DK = Course's Contrubution.

	0	1	2	3	4	5
Level of contribution	None	Very Low	Low	Fair	High	Very High

Event	Quantity	Duration (Hour)	Total Workload (Hour)
Course Duration (Total weeks*Hours per week)	14	2	28
Work Hour outside Classroom (Preparation, strengthening)	14	3	42
Homework	1	6	6
Midterm Exam	1	2	2
Time to prepare for Midterm Exam	1	20	20
Final Exam	1	2	2
Time to prepare for Final Exam	1	20	20
Total Workload
Total Workload / 30 (s)
ECTS Credit of the Course			30