• Basic information
• Learning outcomes
• Contents
• Assessment
• Workload

Learning outcomes

Upon successful completion of this course, students will be able to:

1. develop numerical solutions for basic mathematical operations (interpolation, derivative, integral solution of linear algebraic equations and non linear equations etc.)

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
   2. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
   3. Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.
   4. Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
   5. Using technology as an efficient tool to understand mathematics and apply it.

   Method of assessment

   1. Written exam
2. compute errors in numerical solutions

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
   2. Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.
   3. Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
   4. Using technology as an efficient tool to understand mathematics and apply it.

   Method of assessment

   1. Written exam
3. write computer programming code for numerical solutions

   Contribution to Program Outcomes

   1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
   2. Describing, formulating, and analyzing real-life problems using mathematical and statistical techniques.
   3. Having improved abilities in mathematics communications, problem-solving, and brainstorming skills.
   4. Using technology as an efficient tool to understand mathematics and apply it.

   Method of assessment

   1. Written exam

Contents
Week 1:	Number systems and errors: Representation of integers and fractions.
Week 2:	Floating point arithmetic, loss of significance and error propagation.
Week 3:	Interpolation by polynomial:Polynomial forms, existence and uniqueness of interpolating polynomial.
Week 4:	Interpolation by polynomial: Divided difference table, the error of interpolating polynomial.
Week 5:	Numerical differentiation, numerical integration-some basic rules and Gauss rules.
Week 6:	Numerical integration: Composite rules, adaptive quadrature.
Week 7:	The solution of non-linear equations: A survey of iterative methods, fixed point iteration.
Week 8:	The solution of non-linear equations:Convergence acceleration for fixed point iteration, convergence of Newton and Secant methods.
Week 9:	The solution of non-linear equations: Polynomial equations- real roots, complex roots- Müller method.
Week 10:	Midterm exam and solutions
Week 11:	Matrices and Systems of Linear Equations: Properties of matrices, the solution of linear systems by elimination.
Week 12:	Matrices and Systems of Linear Equations:Pivoting strategies, the triangular factorization.
Week 13:	Matrices and Systems of Linear Equations:Error and residual of an approximate solution; norm.
Week 14:	Matrices and Systems of Linear Equations:Backward-error analysis and iterative improvement, Determinants and the eigenvalue problem.
Week 15*:	-
Week 16*:	Final exam
Textbooks and materials:
Recommended readings:	Elementary Numerical Analysis - An algorithmic Approach, S.D. Conte, Carl de Boor, McGraw Hill, International Series in Pure and Applied Mathemeatics
	* Between 15th and 16th weeks is there a free week for students to prepare for final exam.

Assessment
Method of assessment	Week number	Weight (%)
Mid-terms:	10	40
Other in-term studies:		0
Project:		0
Homework:		0
Quiz:		0
Final exam:	16	60
	Total weight:	(%)

Workload
Activity	Duration (Hours per week)	Total number of weeks	Total hours in term
Courses (Face-to-face teaching):	3	14
Own studies outside class:	3	14
Practice, Recitation:	0	0
Homework:	0	0
Term project:	0	0
Term project presentation:	0	0
Quiz:	0	0
Own study for mid-term exam:	10	1
Mid-term:	3	1
Personal studies for final exam:	20	1
Final exam:	3	1
		Total workload:
		Total ECTS credits:	*
	* ECTS credit is calculated by dividing total workload by 25. (1 ECTS = 25 work hours)