GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
NUMERICAL ANALYSIS/MAT- 311
Course Title: NUMERICAL ANALYSIS
Credits 3 ECTS 4
Semester 5 Compulsory/Elective Compulsory
COURSE INFO
 -- LANGUAGE OF INSTRUCTION
  Turkish
 -- NAME OF LECTURER(S)
  Assoc.Prof.Dr. Fatma AYAZ
 -- WEB SITE(S) OF LECTURER(S)
   http://websitem.gazi.edu.tr/site/fayaz
 -- EMAIL(S) OF LECTURER(S)
  fayaz@gazi.edu.tr
 -- LEARNING OUTCOMES OF THE COURSE UNIT
This course gives new insights to students who have only the knowledge for the solutions of problems analytically since now .
The importance of using computers in many fields such as mathematics, engineering and etc. is also shown effectively
Content of the lecture is associated with the other areas of mathematics such as algebra, analysis etc.
Students have gained knowledge about computer programming and preparing algorithms.
To prepare the sudents for post graduate studies.




 -- MODE OF DELIVERY
  he mode of delivery of this course is Face to face
 -- PREREQUISITES AND CO-REQUISITES
  There is no prerequisite or co-requisite for this course.
 -- RECOMMENDED OPTIONAL PROGRAMME COMPONENTS
  Calculus I,II, Linear Algebra
 --COURSE CONTENT
1. Week  Errors and Computer arithmetic
2. Week  Solution of nonlinear equations:Method of Fixed Point iteration
3. Week  Solution of nonlinear equations:Newton’s Method and convergence of the method
4. Week  Solution of nonlinear equations:Regula Falsi Iteration
5. Week  Solution of nonlinear equations:Method of halving the interval (Bisection method)
6. Week  Newton and Fixed point iteration for the systems of nonlinear equations
7. Week  Solving Sets of Equations:Gauss Elimination and Gauss Jordan Methods
8. Week  midterm Exam
9. Week  Solving Sets of Equations: LU method
10. Week  Solving linear systems by Iterative methods:Jacobi method
11. Week  Solving linear systems by Iterative methods:Gauss-Siedel method
12. Week  Eigen value and Eigen vector Problems: Faddiev-Leverrier method
13. Week  Eigen value and Eigen vector Problems:Vianello iterative approximation method
14. Week  Interpolation: Interpolating polynomials:Newton –Gauss Interpolation formulas
15. Week  Lagrange Interpolation
16. Week  Final Exam
 -- RECOMMENDED OR REQUIRED READING
  • Sayısal Analiz, G. Oturanç, A., Kurnaz, M.., Kiriş, Y., Keskin, Dizgi, Ofset • Numerical Methods for Engineers, Stevan C, Chapra Raymond P. Canale McGraw Hill • An Introduction to Numerical Methods and Analysis, James F. Epperson, John Wiley & Sons • Numerical Analysis Richard L. Burden, J. Douglas Faires Brooks/Cole
 -- PLANNED LEARNING ACTIVITIES AND TEACHING METHODS
  Lecture, Question & Answer, Demonstration, Drill - Practise
 -- WORK PLACEMENT(S)
  None
 -- ASSESSMENT METHODS AND CRITERIA
 
Quantity
Percentage
 Mid-terms
1
30
 Assignment
0
0
 Exercises
2
10
 Projects
0
0
 Practice
0
0
 Quiz
0
0
 Contribution of In-term Studies to Overall Grade  
40
 Contribution of Final Examination to Overall Grade  
60
 -- WORKLOAD
 Efficiency  Total Week Count  Weekly Duration (in hour)  Total Workload in Semester
 Theoretical Study Hours of Course Per Week
14
2
28
 Practising Hours of Course Per Week
14
2
28
 Reading
5
3
15
 Searching in Internet and Library
5
3
15
 Designing and Applying Materials
0
 Preparing Reports
0
 Preparing Presentation
0
 Presentation
0
 Mid-Term and Studying for Mid-Term
1
7
7
 Final and Studying for Final
1
7
7
 Other
0
 TOTAL WORKLOAD: 
100
 TOTAL WORKLOAD / 25: 
4
 ECTS: 
4
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1To train individuals who are contemporary, entrepreneur and have unique and aesthetic values, self-confidence and capable of independent decision-making.X
2To give good education in the program fields as algebra, geometry, applied mathematics, topology and analysis in order to be equipped with enough mathematics.X
3To teach mathematical thinking methods in order to improve the ability to express mathematics both orally and in writing.X
4To train individuals who are knowledgeable about the history of mathematics and the production of scientific knowledge and can follow developments in these disciplines.X
5To provide necessary equipments to take positions such areas as banking, finance, econometrics, and actuarial.X
6To acquire ability to solve problems encountered in real life by means of mathematical modeling using mathematical methods.X
7To provide ability to do necessary resource researches in the areas of mathematics and to use accessed information.X
8To give appropriate training in such areas as in computer programming and creating algorithms in order to take parts in developing IT sector.X
9To gain substructure to be able to study at graduate level.X
10To enable the student to gain the ability of relating mathematics with the other sciences.X