1	Course Title:	NUMERICAL ANALYSIS
2	Course Code:	END3031
3	Type of Course:	Compulsory
4	Level of Course:	First Cycle
5	Year of Study:	3
6	Semester:	5
7	ECTS Credits Allocated:	4
8	Theoretical (hour/week):	2
9	Practice (hour/week) :	0
10	Laboratory (hour/week) :	1
11	Prerequisites:	None
12	Recommended optional programme components:	None
13	Language:	Turkish
14	Mode of Delivery:	Face to face
15	Course Coordinator:	Prof. Dr. NURSEL ÖZTÜRK
16	Course Lecturers:
17	Contactinformation of the Course Coordinator:	nursel@uludag.edu.tr +90 224 2942083 Uludağ Üniversitesi, Endüstri Mühendisliği Bölümü
18	Website:
19	Objective of the Course:	The objective of the course is to learn the numerical analysis methods
20	Contribution of the Course to Professional Development

21

Learning Outcomes:

1 Will be able to understand the solutions for nonlinear and linear systems, regression, interpolation, numerical integration, numerical differentiation methods; 2 Will be able to solve the Engineering problems using the numerical methods; 3 Will be able to use numerical analysis software;

22	Course Content:

Week	Theoretical	Practical
1	Introduction to Numerical Analysis, Error analysis	MATLAB and Numerical Methods Toolkit
2	The solution of nonlinear equations-Bracketing Methods (Graphical methods, The Bisection Method, The False-Position Method)	MATLAB and Numerical Methods Toolkit
3	The solution of nonlinear equations-Open Methods (Simple fixed point iteration, The Newton-Raphson Method	MATLAB and Numerical Methods Toolkit
4	The solution of nonlinear equations (The Secant Method, Multiple roots)	MATLAB and Numerical Methods Toolkit
5	Linear algebraic equations (Motivation, Gauss Elimination, Pitfalls of elimination methods, Techniques for improving solutions, Determinant with Gauss elimination)	MATLAB and Numerical Methods Toolkit
6	Linear algebraic equations (Gauss-Jordan, The matrix inverse, The solution vector with Gauss-Jordan and matrix inverse)	MATLAB and Numerical Methods Toolkit
7	Linear algebraic equations (LU Decomposition, LU Decomposition version of Gauss elimination-Doolittle, Crout decomposition, The matrix inverse with the LU decomposition)	MATLAB and Numerical Methods Toolkit
8	Linear algebraic equations (Cholesky decomposition, Gauss-Seidel method, Jacobi iteration, Convergence criterion for the Gauss-Seidel, Relaxation)	MATLAB and Numerical Methods Toolkit
9	Repeating courses and midterm exam	MATLAB and Numerical Methods Toolkit
10	Least-squares regression, Linear regression, Non-linear regression and linearization, Polynomial regression, Multiple linear regression	Quiz
11	Interpolation (Newton’s divided-difference interpolating polynomials, Lagrange interpolating polynomials	MATLAB and Numerical Methods Toolkit
12	Spline Interpolation (Linear, Quadratic, Cubic Splines)	MATLAB and Numerical Methods Toolkit
13	Numerical Integration (The Trapezoidal Rule, Simpson’s Rules, Integration with unequal segments, Romberg integration)
14	Numerical Differentiation

23	Textbooks, References and/or Other Materials:	S.C. Chapra and R.P. Canale, “Numerical Methods for Engineers”, McGraw Hill
24	Assesment

TERM LEARNING ACTIVITIES	NUMBER	PERCENT
Midterm Exam	1	40
Quiz	1	10
Homeworks, Performances	5	0
Final Exam	1	50
Total	8	100
Contribution of Term (Year) Learning Activities to Success Grade		50
Contribution of Final Exam to Success Grade		50
Total		100
Measurement and Evaluation Techniques Used in the Course
Information

25

ECTS / WORK LOAD TABLE

Activites	NUMBER	TIME [Hour]	Total WorkLoad [Hour]
Theoretical	14	2	28
Practicals/Labs	14	1	14
Self Study and Preparation	12	4	48
Homeworks, Performances	5	5	25
Projects	0	0	0
Field Studies	0	0	0
Midtermexams	1	2	2
Others	1	1	1
Final Exams	1	2	2
Total WorkLoad			120
Total workload/ 30 hr			4
ECTS Credit of the Course			4

26	CONTRIBUTION OF LEARNING OUTCOMES TO PROGRAMME QUALIFICATIONS
PQ1 PQ2 PQ3 PQ4 PQ5 PQ6 PQ7 PQ8 PQ9 PQ10 PQ11 PQ12 PQ13 PQ14 PQ15 PQ16 PQ17 PQ18 PQ19 PQ20 PQ21 PQ22 PQ23 PQ24 LO1 4 4 0 4 0 0 0 4 5 0 0 0 0 0 0 0 LO2 4 4 0 4 0 0 0 4 5 0 0 0 0 0 0 0 LO3 0 0 0 4 0 0 0 4 5 0 0 0 0 0 0 0

LO: Learning Objectives

PQ: Program Qualifications

Contribution Level:

1 Very Low

2 Low

3 Medium

4 High

5 Very High