COURSE UNIT TITLE

: NUMERICAL AND APPROXIMATE METHODS

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
MAT 5102 NUMERICAL AND APPROXIMATE METHODS ELECTIVE 3 0 0 9

Offered By

Graduate School of Natural and Applied Sciences

Level of Course Unit

Second Cycle Programmes (Master's Degree)

Course Coordinator

PROFESSOR DOCTOR BAŞAK KARPUZ

Offered to

STATISTICS (ENGLISH)
M.Sc. Textile Engineering
NATURAL BUILDING STONES AND GEMSTONES
PHYSICS
Mathematics (English)
INDUSTRIAL ENGINEERING - NON THESIS (EVENING PROGRAM) (ENGLISH)
Occupational Healty and Safety
Geothermal Energy
Economic Geology
GEOGRAPHIC INFORMATION SYSTEMS (ENGLISH)
BIOTECHNOLOGY
Computer Science
NAVAL ARCHITECTURE
Computer Engineering Non-Thesis (English)
GEOGRAPHICAL INFORMATION SYSTEMS - NON THESIS (EVENING PROGRAM) (ENGLISH)
Applied Geology
Chemistry
MARINE GEOLOGY AND GEOPHYSICS
ENGINEERING MANAGEMENT- NON THESIS (EVENING PROGRAM)
MARINE CHEMISTRY
Logistics Engineering
M.Sc.Biochemistry
Mathematics (English)
ENVIRONMENTAL EARTH SCIENCES-NON THESIS
Statistics (English)
Mining Operation
M.Sc. Geothermal Energy (Non-Thesis-Evening)
Ph.D. in Biotechnology
Ph.D. in Occupational Health and Safety
Computer Engineering (English)
Statistics (English)
Applied Geology
UNDERWATER ARCHAELOGY
Textile Engineering
GEOGRAPHICAL INFORMATION SYSTEMS (ENGLISH)
Chemistry
Textile Engineering
COMPUTER ENGINEERING (ENGLISH)
Mineral Processing
Mining Operation
Geographical Information Systems (Non-Thesis) (English)
MARINE GEOLOGY AND GEOPHYSICS
Computer Engineering (English)
Mineral Processing
ENVIRONMENTAL EARTH SCIENCES
Ph.D in Biochemistry
Chemistry
Computer Engineering (Non-Thesis-Evening) (English)
Biomedical Tehnologies (English)
Industrial Ph.D. Program In Advanced Biomedical Technologies
Mineral Processing
Economic Geology
MARINE LIVING RESOURCES
PHYSICS
MARINE CHEMISTRY
PHYSICAL OCEANOGRAPHY
EARTHQUAKE MANAGEMENT (Non-Thesis)
EARTHQUAKE MANAGEMENT
ENVIRONMENTAL ENGINEERING (ENGLISH)
Environmental Engineering (English)
Industrial Ph.D. Program In Advanced Biomedical Technologies
Ph.D. in Computer Science (English)
Ph.D. in Biotechnology
Mining Operation

Course Objective

Learning Outcomes of the Course Unit

1   Will be able to adopt the concept of error, converge and stability.
2   Will be able to find Taylor expansion of functions
3   Will be able to find exact or approximate solution of equations.
4   Will be able to find exact or approximate solution of system of equations.
5   Will be able to find a nearest curve to a function that lies on a different space.
6   Will be able to solve Numeriacal Differentiation
7   Will be able to solve Integration

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 Computational and Mathematical Preliminaries
2 Stability and Taylor's Theorem
3 Root finding algorithms, Bisection, Fixed-Point iteration, Newton-Raphson, Secant method
4 The solution of linear systems: Triangular systems, Gauss elimination
5 The solution of linear systems: LU factorization, Tridiagonal systems
6 The solution of linear systems: Iterative methods, Jacobi, Gauss-Seidel
7 The solution of linear systems: Diagonally dominant matrices
8 The solution of linear systems: Algebraic eigenvalue problem
9 Curve fitting: The method of least squares
10 Curve fitting: Interpolation
11 Numerical differentiation
12 Numerical integration

Recomended or Required Reading

John H. Mathews ''Numerical Methods for Mathematics, Science and Engineering''. Prentice-Hall. 1992.

Planned Learning Activities and Teaching Methods

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 MTE MIDTERM EXAM
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE MTE * 0.40 + FIN * 0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) MTE * 0.40 + RST * 0.60


Further Notes About Assessment Methods

None

Assessment Criteria

To be announced.

Language of Instruction

English

Course Policies and Rules

Attending at least 70 percent of lectures is mandatory.

Contact Details for the Lecturer(s)

basak.karpuz@deu.edu.tr

Office Hours

To be announced

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 14 3 42
Preparations before/after weekly lectures 14 7 98
Preparation for midterm exam 1 31 31
Preparation for final exam 1 37 37
Midterm 1 2 2
Final 1 3 3
TOTAL WORKLOAD (hours) 213

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11
LO.1
LO.2333
LO.3
LO.444
LO.53
LO.634
LO.7

CONTACT INFORMATION
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Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

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