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Information
| Unit | FACULTY OF SCIENCE AND LETTERS |
| STATISTICS PR. | |
| Code | ISB301 |
| Name | Numerical Analysis |
| Term | 2017-2018 Academic Year |
| Semester | 5. Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | Türkçe |
| Level | Lisans Dersi |
| Type | Normal |
| Label | E Elective |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. SADULLAH SAKALLIOĞLU |
| Course Instructor |
Prof. Dr. SADULLAH SAKALLIOĞLU
(Güz)
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
Practical knowledge of polynomial interpolation, theoretical knowledge of associated approximation properties
Course Content
Use to approximate definite integrals
Course Precondition
Lineer Eşitliklerin Çözümünde Gauss-Seidel Yöntemini uygulayabilmesi,
Resources
Notes
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Make solutions to systems of linear equations |
| LO02 | Apply Gauss Elimination and Gauss-Jordan Methods for Solving Linear Equations |
| LO03 | Apply Gauss-Siedel Methods for solving linear equations |
| LO04 | Find Root of a function |
| LO05 | Find polynomial interpolation, |
| LO06 | Use to approximate definite integrals |
| LO07 | Examines errors in calculations |
| LO08 | Apply least squares method |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | Explain the essence fundamentals and concepts in the field of Statistics | |
| PLO02 | Bilgi - Kuramsal, Olgusal | Emphasize the importance of Statistics in life | 2 |
| PLO03 | Bilgi - Kuramsal, Olgusal | Define basic principles and concepts in the field of Law and Economics | |
| PLO04 | Bilgi - Kuramsal, Olgusal | Produce numeric and statistical solutions in order to overcome the problems | |
| PLO05 | Bilgi - Kuramsal, Olgusal | Use proper methods and techniques to gather and/or to arrange the data | |
| PLO06 | Bilgi - Kuramsal, Olgusal | Utilize computer programs and builds models, solves problems, does analyses and comments about problems concerning randomization | |
| PLO07 | Bilgi - Kuramsal, Olgusal | Apply the statistical analyze methods | 2 |
| PLO08 | Bilgi - Kuramsal, Olgusal | Make statistical inference (estimation, hypothesis tests etc.) | |
| PLO09 | Bilgi - Kuramsal, Olgusal | Generate solutions for the problems in other disciplines by using statistical techniques and gain insight | |
| PLO10 | Bilgi - Kuramsal, Olgusal | Discover the visual, database and web programming techniques and posses the ability of writing programs | |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Distinguish the difference between the statistical methods | |
| PLO12 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Make oral and visual presentation for the results of statistical methods | |
| PLO13 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | Have capability on effective and productive work in a group and individually | 4 |
| PLO14 | Yetkinlikler - Bağımsız Çalışabilme ve Sorumluluk Alabilme Yetkinliği | 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 | 2 |
| PLO15 | Yetkinlikler - Öğrenme Yetkinliği | Develop scientific and ethical values in the fields of statistics-and scientific data collection |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 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 | Midterm 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 | Written Exam | |
| 16 | Final exam | Rewview the topics discussed in the lecture notes and sources | |
| 17 | Final exam | Rewview the topics discussed in the lecture notes and sources |
Assessment (Exam) Methods and Criteria
| Assessment Type | Midterm / Year Impact | End of Term / End of Year Impact |
|---|---|---|
| 1. Midterm Exam | 100 | 40 |
| General Assessment | ||
| Midterm / Year Total | 100 | 40 |
| 1. Final Exam | - | 60 |
| Grand Total | - | 100 |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||