| Course Title | Code | Language | Type | Semester | L+U Hour | Credits | ECTS |
|---|---|---|---|---|---|---|---|
| Probability And Biostatistics | BMM221 | Turkish | Compulsory | 3. Semester | 3 + 0 | 3.0 | 4.0 |
| Prerequisite Courses | |
| Course Level | Undergraduate |
| Mode of delivery | Face-to-Face Education |
| Course Coordinator | Doç. Dr. Emine GÜVEN |
| Instructor(s) | Doç. Dr. Emine GÜVEN (Güz) |
| Goals | To provide an understanding of randomness, to give some concepts of probability theory and to create a probability language for introduction to statistical theory. |
| Course Content | Some tools for modeling problems involving randomness and discrete probability distributions and their applications. |
| # | Öğrenme Kazanımı |
| 1 | Explains and applies basic methods of counting. |
| 2 | Explains binomial theory. |
| 3 | Explains concepts and ideas related to probability. |
| 4 | Solves problems related to conditional probability using Bayes theorem. |
| 5 | Explains probability distributions and their properties using computer simulations. |
| 6 | Uses information and communication technologies in modeling probability situations. |
| 7 | Demonstrates a positive attitude towards probability. |
| 8 | Appreciates the importance of probability knowledge in real life. |
| Week | Topics/Applications | Method |
|---|---|---|
| 1. Week | History of Probability, Introduction to Probability. Counting Methods, | Class Hours |
| 2. Week | Probability Axioms, Conditional Probability, Independent Events | Class Hours |
| 3. Week | Random Variables, Joint Probability Distributions | Class Hours |
| 4. Week | Mathematical Expextation of random variable | Class Hours |
| 5. Week | Variance and Covariance of Random Variables | Class Hours |
| 6. Week | Means and Variances of Linear Combinations of Random Variables | Class Hours |
| 7. Week | Moments and Moment-Generating Functions | Class Hours |
| 8. Week | Chebyshev's Inequality and the Law of Large Numbers | |
| 9. Week | Midterm exam, and Chebyshev's Inequality and the Law of Large Numbers | Class Hours |
| 10. Week | Important Discrete Distribution Functions | Class Hours |
| 11. Week | Hypergeometric Distribution | Class Hours |
| 12. Week | Poisson Distribution | Class Hours |
| 13. Week | Continuous Uniform Distribution | |
| 14. Week | Normal Distribution, Sampling Theory | Class Hours |
| Program Requirements | DK1 | DK2 | DK3 | DK4 | DK5 | DK6 | DK7 | DK8 |
|---|
| Ders Kitabı veya Notu | Ders Kitabı veya Ders Notu bulunmamaktadır. |
|---|---|
| Diğer Kaynaklar |
|
| ECTS credits and course workload | Quantity | Duration (Hour) | Total Workload (Hour) | |
|---|---|---|---|---|
|
Ders İçi |
Class Hours | 14 | 3 | 42 |
|
Sınavlar |
Midterm 1 | 1 | 1 | 1 |
| Practice End-Of-Term | 1 | 1 | 1 | |
| Total Workload | 44 | |||
| *AKTS = (Total Workload) / 25,5 | ECTS Credit of the Course | 4.0 | ||
