| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Probability And Statistics | CE106 | English | Compulsory | 2. Semester | 3 + 0 | 3.0 | 4.0 |
| Prerequisite Courses | |
| Course Level | Undergraduate |
| Mode of delivery | Lecture, Presentation, Problem Solving, Discussion |
| Course Coordinator | Prof. Dr. ALİ ÇALHAN |
| Instructor(s) | |
| Goals | Teaching probability theory and statistics |
| Course Content | Probability theory, random variables, variable families, statistics topics |
| # | Öğrenme Kazanımı |
| 1 | To be able to understand and relate the concepts of probability theory and set theory |
| 2 | To be able to comprehend probability axioms, conditional probability and bayes' theorem |
| 3 | To be able to understand the subject of events and independent events, to use sequential experiments and tree diagrams. |
| 4 | Understanding of counting methods and independent trials |
| 5 | To be able to understand the concepts of random variable and discrete random variable |
| 6 | To be able to understand the mass function and cumulative distribution function of discrete random variable families. |
| 7 | Ability to calculate mean, expected value, moment, variance and standard deviation in discrete random variables |
| 8 | To be able to understand the density function and cumulative distribution function of continuous random variable families. |
| 9 | Ability to calculate mean, expected value, moment, variance and standard deviation values in continuous random variables |
| 10 | To be able to comprehend the concepts of correlation and covariance with functions of random variable pairs. |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | set theory and probability theory | |
| 2. Week | Probability axioms, conditional probability and Bayes' theorem | |
| 3. Week | Independent events, sequential experiments, and tree diagrams | |
| 4. Week | Counting methods and independent trials | |
| 5. Week | Random variable concept and discrete random variables | |
| 6. Week | Discrete random variable families | |
| 7. Week | Probability mass function and cumulative distribution function in discrete random variables | |
| 8. Week | Mean, expected value, moment, variance and standard deviation in discrete random variables | |
| 9. Week | Continuous random variables | |
| 10. Week | Probability density function and cumulative distribution function in continuous random variables | |
| 11. Week | Continuous random variable families | |
| 12. Week | Mean, expected value, moment, variance and standard deviation in continuous random variables | |
| 13. Week | Random variable pairs and expected value | |
| 14. Week | Functions, correlation and covariance of random variable pairs |
| Program Requirements | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 | DK8 | DK9 | DK10 |
|---|
| Ders Kitabı veya Notu | Ders Kitabı veya Ders Notu bulunmamaktadır. |
|---|---|
| Diğer Kaynaklar |
|
| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Sınavlar |
Midterm 1 | 5 | 16 | 80 |
| Homework 1 | 3 | 8 | 24 | |
| Total Workload | 104 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 4.0 | ||
