Computer Engineering
Course Details
KTO KARATAY UNIVERSITY
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Computer Engineering
Course Details
Mühendislik ve Doğa Bilimleri Fakültesi
Programme of Computer Engineering
Course Details
| Course Code | Course Name | Year | Period | Semester | T+A+L | Credit | ECTS |
|---|---|---|---|---|---|---|---|
| 05030001 | Probability and Statistics | 2 | Autumn | 3 | 3+0+0 | 3 | 5 |
| Course Type | Compulsory |
| Course Cycle | Bachelor's (First Cycle) (TQF-HE: Level 6 / QF-EHEA: Level 1 / EQF-LLL: Level 6) |
| Course Language | Turkish |
| Methods and Techniques | - |
| Mode of Delivery | Face to Face |
| Prerequisites | - |
| Coordinator | - |
| Instructor(s) | Asst. Prof. Vahdettin DEMİR |
| Instructor Assistant(s) | - |
Course Instructor(s)
| Name and Surname | Room | E-Mail Address | Internal | Meeting Hours |
|---|---|---|---|---|
| Asst. Prof. Vahdettin DEMİR | A- | [email protected] |
Course Content
Klasik sonlu uzay olasılığı, olasılıksal koşullara yaklaşım. Bayes teoremi. Olayların bağımsızlığı. Bazı olasılık modelleri. Ölçülebilir fonksiyonlar ve rasgele değişkenler. Dağılımları. Ayrık ve kesinlikle sürekli dağılımlar. Rastgele değişkenlerin dönüşümleri. Koşullu dağılımlar. Matematiksel beklentiler: ortalama, varyans, moment üreten fonksiyonlar. Özellikleri fonksiyonları. Koşullu beklenti. Sınırlı dağılımlar
Objectives of the Course
The course aims to teach the probability axioms, distribution and characteristic functions and mathematical expectations to the students
Contribution of the Course to Field Teaching
| Basic Vocational Courses | X |
| Specialization / Field Courses | |
| Support Courses | |
| Transferable Skills Courses | |
| Humanities, Communication and Management Skills Courses |
Relationships between Course Learning Outcomes and Program Outcomes
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Program Learning Outcomes | Level |
|---|---|---|
| P1 | Adequate knowledge in mathematics, science and related engineering discipline accumulation; theoretical and practical knowledge in these areas, complex engineering the ability to use in problems. | 5 |
Course Learning Outcomes
| Upon the successful completion of this course, students will be able to: | |||
|---|---|---|---|
| No | Learning Outcomes | Outcome Relationship | Measurement Method ** |
| O1 | Knows the applications of mathematics in engineering | P.1.4 | 1 |
| O2 | Knows numerical calculations and analysis | P.1.5 | 1 |
| ** Written Exam: 1, Oral Exam: 2, Homework: 3, Lab./Exam: 4, Seminar/Presentation: 5, Term Paper: 6, Application: 7 | |||
Weekly Detailed Course Contents
| Week | Topics |
|---|---|
| 1 | The classical finite space approach to probability, conditional probability. |
| 2 | Bayes theorem. |
| 3 | Independence of events |
| 4 | Some probability models. |
| 5 | Measurable functions and random variables. |
| 6 | Distributions. Discrete and absolutely continuous distributions. |
| 7 | Transformations of random variables. |
| 8 | Conditional distributions. |
| 9 | Mathematical expectations: mean, variance, moment generating functions. |
| 10 | Characteristics functions. |
| 11 | Conditional expectation. |
| 12 | Limiting distributions |
Textbook or Material
| Resources | Jean Jacod and Phillip Protter "Probability Essentials", Springer, 2nd Edition, (2003) |
Evaluation Method and Passing Criteria
| In-Term Studies | Quantity | Percentage |
|---|---|---|
| Attendance | - | - |
| Laboratory | - | - |
| Practice | - | - |
| Course Specific Internship (If Any) | - | - |
| Homework | - | - |
| Presentation | - | - |
| Projects | - | - |
| Quiz | - | - |
| Midterms | 1 | 40 (%) |
| Final Exam | 1 | 60 (%) |
| Total | 100 (%) | |
ECTS / Working Load Table
| Quantity | Duration | Total Work Load | |
|---|---|---|---|
| Course Week Number and Time | 14 | 3 | 42 |
| Out-of-Class Study Time (Pre-study, Library, Reinforcement) | 14 | 3 | 42 |
| Midterms | 1 | 33 | 33 |
| Quiz | 0 | 0 | 0 |
| Homework | 0 | 0 | 0 |
| Practice | 0 | 0 | 0 |
| Laboratory | 0 | 0 | 0 |
| Project | 0 | 0 | 0 |
| Workshop | 0 | 0 | 0 |
| Presentation/Seminar Preparation | 0 | 0 | 0 |
| Fieldwork | 0 | 0 | 0 |
| Final Exam | 1 | 33 | 33 |
| Other | 0 | 0 | 0 |
| Total Work Load: | 150 | ||
| Total Work Load / 30 | 5 | ||
| Course ECTS Credits: | 5 | ||
Course - Learning Outcomes Matrix
| Relationship Levels | ||||
| Lowest | Low | Medium | High | Highest |
| 1 | 2 | 3 | 4 | 5 |
| # | Learning Outcomes | P1 |
|---|---|---|
| O1 | Knows the applications of mathematics in engineering | 4 |
| O2 | Knows numerical calculations and analysis | 5 |