# GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
NUMERICAL ANALYSIS/CE343
 Course Title: NUMERICAL ANALYSIS Credits 3 ECTS 3 Course Semester 5 Type of The Course Compulsory
COURSE INFORMATION
-- (CATALOG CONTENT)
-- (TEXTBOOK)
-- (SUPPLEMENTARY TEXTBOOK)
-- (PREREQUISITES AND CO-REQUISITES)
-- LANGUAGE OF INSTRUCTION
English
-- COURSE OBJECTIVES
-- COURSE LEARNING OUTCOMES
An ability to use numerical methods
Modelling of engineering problems and development of solution strategies using numerical methods accordance with this model
Finding solution using numerical methods for differential equations that do not have any analytical solution
Computer programming application on engineering problems
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-- MODE OF DELIVERY
The mode of delivery of this course is Face to face
 --WEEKLY SCHEDULE 1. Week Introduction, Mathematical Modelling, Error Analysis 2. Week Roots of Equations 1: Bracketing Methods;Graphical Methods, The Bisection Method, The False Position Method 3. Week Roots of Equations 2: Open Methods; Simple Fixed-Point Iteration, The Newton Raphson Method, The Secant Method Systems of Nonlinear Equations 4. Week Linear Algebraic Equations 1: Gauss Elimination, Gauss- Seidel, Gauss-Jordan Methods 5. Week Linear Algebraic Equations 2: L-U Decomposition and Matrix Inverse 6. Week Curve Fitting 1: Least-Squares Regression; Linear Regression, Polynomial Regression, Multiple Linear Regression, Nonlinear Regression 7. Week Curve Fitting 2: Interpolation; Newton's Divided-Difference Interpolating Polynomials, Lagrange Interpolating Polynomial 8. Week Curve Fitting 2: Interpolation; Newton's Divided-Difference Interpolating Polynomials, Lagrange Interpolating Polynomial and Mid-Term Examination I 9. Week Numerical Integration 1: Newton Cotes Integration Formulas: The Trapezoidal Rule, Simpson's Rule 10. Week Numerical Integration 2: Multiple Integrals, Improper Integrals, Numerical Differentiation:High-Accuracy Differentiation Formulae,Partial Derivatives 11. Week Ordinary Differential Equations 1: Euler's Method, Improvements of Euler's Method, Runge-Kutta Methods 12. Week Ordinary Differential Equations 2: Systems of Equations, Boundary-Value and Eigenvalue Problems 13. Week Partial Differential Equations 1: Finite Difference and Elliptic Equations 14. Week Partial Differential Equations 2: Finite Difference and Parabolic Equations 15. Week Mid-Term Examination II 16. Week -
-- TEACHING and LEARNING METHODS
-- ASSESSMENT CRITERIA
 Quantity Total Weighting (%) Midterm Exams 2 50 Assignment 6 10 Application 0 0 Projects 0 0 Practice 0 0 Quiz 0 0 Percent of In-term Studies 60 Percentage of Final Exam to Total Score 40