| Course Title | Code | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|
| Probability And Statistics | CE106 | 2. Semester | 3 + 0 | 3.0 | 4.0 |
| Prerequisites | None |
| Language of Instruction | English |
| Course Level | Undergraduate |
| Course Type | |
| Mode of delivery | Lecture, Presentation, Problem Solving, Discussion |
| Course Coordinator |
Prof. Dr. ALİ ÇALHAN |
| Instructors |
ALİ ÇALHAN |
| Assistants | |
| Goals | Teaching probability theory and statistics |
| Course Content | Probability theory, random variables, variable families, statistics topics |
| Learning Outcomes |
- To be able to understand and relate the concepts of probability theory and set theory - To be able to comprehend probability axioms, conditional probability and bayes' theorem - To be able to understand the subject of events and independent events, to use sequential experiments and tree diagrams. - Understanding of counting methods and independent trials - To be able to understand the concepts of random variable and discrete random variable - To be able to understand the mass function and cumulative distribution function of discrete random variable families. - Ability to calculate mean, expected value, moment, variance and standard deviation in discrete random variables - To be able to understand the density function and cumulative distribution function of continuous random variable families. - Ability to calculate mean, expected value, moment, variance and standard deviation values in continuous random variables - To be able to comprehend the concepts of correlation and covariance with functions of random variable pairs. |
| Week | Topics | Learning Methods |
|---|---|---|
| 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 |
| Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers (Roy D. Yates, David J. Goodman) |
| Program Requirements | Contribution Level | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 | DK8 | DK9 | DK10 | Measurement Method |
|---|
| 0 | 1 | 2 | 3 | 4 | 5 | |
|---|---|---|---|---|---|---|
| Course's Level of contribution | None | Very Low | Low | Fair | High | Very High |
| Method of assessment/evaluation | Written exam | Oral Exams | Assignment/Project | Laboratory work | Presentation/Seminar |
| Event | Quantity | Duration (Hour) | Total Workload (Hour) |
|---|---|---|---|
| Midterm 1 | 5 | 16 | 80 |
| Homework 1 | 3 | 8 | 24 |
| Total Workload | 104 | ||
| ECTS Credit of the Course | 4.0 | ||
