GAZI UNIVERSITY INFORMATION PACKAGE - 2019 ACADEMIC YEAR

COURSE DESCRIPTION
INTRODUCTION TO NUMERICAL ANALYSIS/ME313
Course Title: INTRODUCTION TO NUMERICAL ANALYSIS
Credits 3 ECTS 4
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
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
 --WEEKLY SCHEDULE
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
8. Week  CURVE FITTING: Interpolation methods: quadratic spline interpolation.Cubic spline interpolation.
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  NUMERICAL DIFFERENTIATION: Derivatives of unequally spaced data.
13. Week  NUMERICAL SOLUTION OF ORDINARY DIFFERENTIAL EQUATIONS: Euler’s method, Runge–Kutta methods.
14. Week  NUMERICAL SOLUTION OF PARTIAL DIFFERENTIAL EQUATIONS
15. Week  Final
16. Week  Final
 -- TEACHING and LEARNING METHODS
 -- ASSESSMENT CRITERIA
 
Quantity
Total Weighting (%)
 Midterm Exams
2
50
 Assignment
5
5
 Application
0
0
 Projects
0
0
 Practice
2
0
 Quiz
3
5
 Percent of In-term Studies  
60
 Percentage of Final Exam to Total Score  
40
 -- WORKLOAD
 Activity  Total Number of Weeks  Duration (weekly hour)  Total Period Work Load
 Weekly Theoretical Course Hours
14
3
42
 Weekly Tutorial Hours
0
 Reading Tasks
8
1
8
 Searching in Internet and Library
10
2
20
 Material Design and Implementation
0
 Report Preparing
0
 Preparing a Presentation
0
 Presentation
0
 Midterm Exam and Preperation for Midterm Exam
2
10
20
 Final Exam and Preperation for Final Exam
1
10
10
 Other (should be emphasized)
0
 TOTAL WORKLOAD: 
100
 TOTAL WORKLOAD / 25: 
4
 Course Credit (ECTS): 
4
 -- COURSE'S CONTRIBUTION TO PROGRAM
NO
PROGRAM LEARNING OUTCOMES
1
2
3
4
5
1Adequate knowledge in mathematics, science and engineering subjects pertaining to the relevant discipline; ability to use theoretical and applied knowledgein these areas in complex engineering problems.X
2Ability to identify, formulate, and solve complex engineering problems; ability to select and apply proper analysis and modeling methods for this purpose.X
3Ability to design a complex system, process, device or product under realistic constraints and conditions, in such a way as to meet the desired result; ability to apply modern design methods for this purpose.X
4Ability to devise, select, and use modern techniques and tools needed for analyzing and solving complex problems encountered in engineering practice; ability to employ information technologies effectively.X
5Ability to design and conduct experiments, gather data, analyze and interpret results for investigating complex engineering problems or discipline specific research questions.X
6Ability to work efficiently in intra-disciplinary and multi-disciplinary teams; ability to work individually.X
7Ability to communicate effectively in Turkish, both orally and in writing; knowledge of a minimum of one foreign language; ability to write effective reports and comprehend written reports, prepare design and production reports, make effective presentations, and give and receive clear and intelligible instructions.X
8Recognition of the need for lifelong learning; ability to access information, to follow developments in science and technology, and to continue to educate him/herself.X
9Consciousness to behave according to ethical principles and professional and ethical responsibility; knowledge on standards used in engineering practice.X
10Knowledge about business life practices such as project management, risk management, and change management; awareness in entrepreneurship, innovation; knowledge about sustainable development.X
11Knowledge about the global and social effects of engineering practices on health, environment, and safety, and contemporary issues of the century reflected into the field of engineering; awareness of the legal consequences of engineering solutions.X
 -- NAME OF LECTURER(S)
   (Assist. Prof. Dr. Nureddin DİNLER , Assist. Prof. Dr. Tolga PIRASACI )
 -- WEB SITE(S) OF LECTURER(S)
   (https://websitem.gazi.edu.tr/site/ndinler , https://websitem.gazi.edu.tr/site/pirasaci)
 -- EMAIL(S) OF LECTURER(S)
   (ndinler@gazi.edu.tr , pirasaci@gazi.edu.tr)