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Syllabus ( MATH 311 )


   Basic information
Course title: Numerical Analysis II
Course code: MATH 311
Lecturer: Assoc. Prof. Dr. Hülya ÖZTÜRK
ECTS credits: 6
GTU credits: 0 (3+0+0)
Year, Semester: 3, Spring
Level of course: First Cycle (Undergraduate)
Type of course: Departmental Elective
Language of instruction: English
Mode of delivery: Face to face
Pre- and co-requisites: Math 113
Professional practice: No
Purpose of the course: Students who can successfully complete this course are equipped with the skills to analyze various aspects, such as numerical integration the solutions of ordinary differential equations and to draw appropriate conclusions in practical applications.
   Learning outcomes Up

Upon successful completion of this course, students will be able to:

  1. They obtain a wide knowledge numerical integration and the numerical solutions of ordinary differential equations.

    Contribution to Program Outcomes

    1. Having the knowledge about the scope, applications, history, problems, and methodology of mathematics that are useful to humanity both as a scientific and as an intellectual discipline.
    2. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
    3. Adapt to a fast-changing technological environment, improving their knowledge and abilities constantly.
    4. Using technology as an efficient tool to understand mathematics and apply it.

    Method of assessment

    1. Written exam
  2. The can use the programing language Matlab efficiently in order to compute the numerical solutions and/or approximations.

    Contribution to Program Outcomes

    1. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
    2. Adapt to a fast-changing technological environment, improving their knowledge and abilities constantly.
    3. Using technology as an efficient tool to understand mathematics and apply it.

    Method of assessment

    1. Written exam
  3. They can use the theoratical results in various applications.

    Contribution to Program Outcomes

    1. Communicating between mathematics and other disciplines, and building mathematical models for interdisciplinary problems.
    2. Adapt to a fast-changing technological environment, improving their knowledge and abilities constantly.
    3. Using technology as an efficient tool to understand mathematics and apply it.
    4. Exhibiting professional and ethical responsibility.

    Method of assessment

    1. Homework assignment
   Contents Up
Week 1: Numerical Differentiation
Week 2: Numerical Differentiation
Week 3: Numerical Differentiation - Matlab Application
Week 4: Numerical İntegration
Week 5: Gaussian Quadrature
Week 6: Numerical Integration and Gaussian Quadrature - Matlab Application
Week 7: Initial-Value Problems for Ordinary Differential Equations
Euler’s Method
Week 8: Midterm and Solutions
Week 9: Higher-Order Taylor Methods
Week 10: Initial-Value Problems for ODEs -Matlab Application
Week 11: Higher-Order Equations and Systems of Differential Equations
Week 12: Boundary Value Problems for ODEs
Week 13: Boundary Value Problems for ODEs
Week 14: Higher-Order Equations and Systems of Differential Equations and Boundary Value Problems for ODEs- Matlab Application
Week 15*: -
Week 16*: Final Exam
Textbooks and materials: Richard L. Burden, John Dougles, Numerical Analysis
Ward Cheney, David Kincaid, Numerical Mathematics and Computing
Endre Süli, David F. Mayers, An Introduction to Numerical Analysis
Recommended readings: Richard L. Burden, John Dougles, Numerical Analysis
Ward Cheney, David Kincaid, Numerical Mathematics and Computing
Endre Süli, David F. Mayers, An Introduction to Numerical Analysis
  * Between 15th and 16th weeks is there a free week for students to prepare for final exam.
Assessment Up
Method of assessment Week number Weight (%)
Mid-terms: 8 40
Other in-term studies: 0
Project: 0
Homework: 0
Quiz: 0
Final exam: 16 60
  Total weight:
(%)
   Workload Up
Activity Duration (Hours per week) Total number of weeks Total hours in term
Courses (Face-to-face teaching): 3 14
Own studies outside class: 6 14
Practice, Recitation: 0 0
Homework: 0 0
Term project: 0 0
Term project presentation: 0 0
Quiz: 0 0
Own study for mid-term exam: 10 1
Mid-term: 2 1
Personal studies for final exam: 10 1
Final exam: 2 1
    Total workload:
    Total ECTS credits:
*
  * ECTS credit is calculated by dividing total workload by 25.
(1 ECTS = 25 work hours)
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