# GAZI UNIVERSITY INFORMATION PACKAGE - 2018 ACADEMIC YEAR

COURSE DESCRIPTION
INTRODUCTION TO NUMERICAL ANALYSIS/MM 313 E
 Course Title: INTRODUCTION TO NUMERICAL ANALYSIS Credits 3 ECTS 4 Semester 5 Compulsory/Elective Compulsory
COURSE INFO
-- LANGUAGE OF INSTRUCTION
English
-- NAME OF LECTURER(S)
Assist.Prof. Ezgi GÜNAY, Assoc.Prof.Dr.Nureddin Dinler, Instr.Dr.Tunç APATAY, Instr.Dr.Tolga PIRASACI
-- WEB SITE(S) OF LECTURER(S)
websitem.gazi.edu.tr/egunay, websitem.gazi.edu.tr/ndinler, websitem.gazi.edu.tr/site/tapatay, websitem.gazi.edu.tr/pirasaci
-- EMAIL(S) OF LECTURER(S)
egunay@gazi.edu.tr, ndinler@gazi.edu.tr,tapatay@gazi.edu.tr, pirasaci@gazi.edu.tr
-- LEARNING OUTCOMES OF THE COURSE UNIT
Understanding and application of the methods to find the roots of an equations.
Students are expected to be able to apply basic numerical methods about the system of linear algebraic equations.
Students are expected to understand and apply the curve fitting methods.
Students are expected to understand and apply the basic knowledge of numerical differentiation and integration.
Students are expected to understand and apply the basic knowledge of numerical solution of differential equations.

-- MODE OF DELIVERY
The 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
MM 102 Mühendislikte Programlamaya Giriş
 --COURSE CONTENT 1. Week INTRODUCTION: Numerical methods used for problem solving. Steps in solving a problem with a computer. Mathematical modelling. 2. Week ROOTS OF EQUATIONS: Graphical methods. Bracketing methods: Bisection and false-position methods. 3. Week ROOTS OF EQUATIONS: Open methods: Simple one-point iteration, Newton–Raphson, secant and modified Newton–Raphson methods. 4. Week SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS: Introduction. Methods for solving systems of linear algebraic equations. Gauss elimination method. 5. Week SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS: Matrix inversion method. Gauss-Seidel method. LU decomposition methods 6. Week CURVE FITTING: Introduction. Least square regression: Linear regression, polynomial regression and multiple linear regression. 7. Week CURVE FITTING: Interpolation methods: Newton Interpolation, Lagrange interpolation, quadratic spline interpolation.Cubic spline interpolation. 8. Week MIDTERM EXAM I. 9. Week NUMERICAL INTEGRATION: Introduction. Numerical integration methods: Newton–Cotes formulas, trapezoidal rule. 10. Week NUMERICAL INTEGRATION: Simpson’s rules: Simpson’s 1/3 rule, Simpson’s 3/8 rule. 11. Week NUMERICAL DIFFERENTIATION: Introduction. Finite difference approximations of the first and the second derivatives: Forward, backward and central diff 12. Week MIDTERM EXAM II. 13. Week NUMERICAL DIFFERENTIATION: Derivatives of unequally spaced data. 14. Week NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS: Euler’s method, Runge–Kutta methods. 15. Week NUMERICAL SOLUTION OF PARTIAL DIFFERENTIAL EQUATIONS 16. Week FINAL