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•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Numerical Analysis * ISB   301 5 3 3 6

 Prerequisites and co-requisites Lineer Eşitliklerin Çözümünde Gauss-Seidel Yöntemini uygulayabilmesi, Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Instructors
 Prof.Dr. SADULLAH SAKALLIOĞLU 1. Öğretim Grup:A Prof.Dr. SADULLAH SAKALLIOĞLU 2. Öğretim Grup:A

Assistants
Goals
Practical knowledge of polynomial interpolation, theoretical knowledge of associated approximation properties
Content
Use to approximate definite integrals

Learning Outcomes
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Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Explain the essence fundamentals and concepts in the field of Probability, Statistics and Mathematics
2
Emphasize the importance of Statistics in life
3
Define basic principles and concepts in the field of Law and Economics
4
Produce numeric and statistical solutions in order to overcome the problems
X
5
Use proper methods and techniques to gather and/or to arrange the data
X
6
Utilize computer systems and softwares
X
7
Construct the model, solve and interpret the results by using mathematical and statistical tehniques for the problems that include random events
X
8
Apply the statistical analyze methods
X
9
Make statistical inference(estimation, hypothesis tests etc.)
10
Generate solutions for the problems in other disciplines by using statistical techniques
X
11
Discover the visual, database and web programming techniques and posses the ability of writing programme
X
12
Construct a model and analyze it by using statistical packages
13
Distinguish the difference between the statistical methods
14
Be aware of the interaction between the disciplines related to statistics
X
15
Make oral and visual presentation for the results of statistical methods
X
16
Have capability on effective and productive work in a group and individually
X
17
Professional development in accordance with their interests and abilities, as well as the scientific, cultural, artistic and social fields, constantly improve themselves by identifying training needs
18
Develop scientific and ethical values in the fields of statistics-and scientific data collection
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Meaning of numerical analysis, number systems, and general information about the error, Source reading
2 Methods of Solving Nonlinear Equations; bisection and Newton methods Source reading
3 Methods of Solving Nonlinear Equations, Regula-Falsi and Bairstow methods, Source reading
4 Systems of linear equations, matrix inverse and determinant Source reading
5 Solving Linear Equations; Gauss Elimination and Gauss-Jordan Methods Source reading
6 Gauss Elimination and Gauss-Jordan Methods for finding inverse of the matrix and determinant. Source reading
7 Gauss-Seidel Method of Solving Linear Equations Source reading
8 Mid-term exam Rewview the topics discussed in the lecture notes and sources
9 Interpolation, linear interpolation, Lagrange Interpolation Source reading
10 Central difference interpolation Source reading
11 Forward difference interpolation Source reading
12 Backward difference interpolation Source reading
13 Numerical integration methods Source reading
14 Curve fitting, method of least squares Source reading
15 Final Exam Rewview the topics discussed in the lecture notes and sources
16-17 Final exam Rewview the topics discussed in the lecture notes and sources