Faculty Of Engıneerıng
Electrıcal And Electronıcs Engıneerıng (Englısh)
Course Information
| PROBABILITY AND RANDOM VARIABLES | |||||
|---|---|---|---|---|---|
| Code | Semester | Theoretical | Practice | National Credit | ECTS Credit |
| Hour / Week | |||||
| EEE208 | Spring | 3 | 0 | 3 | 4 |
| Prerequisites and co-requisites | Prof. Dr. Adnan MAZMANOĞLU |
|---|---|
| Language of instruction | English |
| Type | Required |
| Level of Course | Bachelor's |
| Lecturer | |
| Mode of Delivery | Face to Face |
| Suggested Subject | |
| Professional practise ( internship ) | None |
| Objectives of the Course | Help students learn, understand, explain, and use concepts about probability, and to prepare them for further study in engineering. |
| Contents of the Course | Counting Techniques, Addition and Multiplication Rules, Bayes Theorem, Distributions (Normal, Binom, Poisson etc.) |
Learning Outcomes of Course
| # | Learning Outcomes |
|---|---|
| 1 | Getting knowledge about Interpretations and Axioms of Probability |
| 2 | Getting knowledge about Multiplication and Total Probability Rules, Independence and Bayes' Theorem |
| 3 | Getting knowledge about Cumulative Distribution Functions, Binomial Distribution |
| 4 | Getting knowledge about Sample Spaces and Events, Probability and Probability Models, |
Course Syllabus
| # | Subjects | Teaching Methods and Technics |
|---|---|---|
| 1 | Probability and Probability Models | Lecture |
| 2 | Sample Spaces and Events | Lecture |
| 3 | Counting Techniques | Lecture |
| 4 | Interpretations and Axioms of Probability | Lecture |
| 5 | Addition Rules and Conditional Probability | Lecture |
| 6 | Multiplication and Total Probability Rules | Lecture |
| 7 | Independence and Bayes' Theorem | Lecture |
| 8 | Midterm Exam | |
| 9 | Random Variables: Discrete and Continuous | Lecture |
| 10 | Cumulative Distribution Functions | Lecture |
| 11 | Mean and Variance of a Discrete Random Variable | Lecture |
| 12 | Binomial Distribution | Lecture |
| 13 | Geometric and Negative Binomial Distributions | Lecture |
| 14 | Poisson Distribution | Lecture |
| 15 | Normal Distribution | Lecture |
| 16 | Final Exam |
Course Syllabus
| # | Material / Resources | Information About Resources | Reference / Recommended Resources |
|---|---|---|---|
| 1 | Douglas C. Montgomery and George C. Runger, Applied Statistics and Probability for Engineers, Sixth Edition, John Wiley & Sons, 2014, ISBN-13 9781118539712. |
Method of Assessment
| # | Weight | Work Type | Work Title |
|---|---|---|---|
| 1 | 40% | Mid-Term Exam | Mid-Term Exam |
| 2 | 60% | Final Exam | Final Exam |
Relationship between Learning Outcomes of Course and Program Outcomes
| # | Learning Outcomes | Program Outcomes | Method of Assessment |
|---|---|---|---|
| 1 | Getting knowledge about Interpretations and Axioms of Probability | 1 | 1͵2 |
| 2 | Getting knowledge about Multiplication and Total Probability Rules, Independence and Bayes' Theorem | 1 | 1͵2 |
| 3 | Getting knowledge about Cumulative Distribution Functions, Binomial Distribution | 1 | 1͵2 |
| 4 | Getting knowledge about Sample Spaces and Events, Probability and Probability Models, | 1 | 1͵2 |
Work Load Details
| # | Type of Work | Quantity | Time (Hour) | Work Load |
|---|---|---|---|---|
| 1 | Course Duration | 14 | 3 | 42 |
| 2 | Course Duration Except Class (Preliminary Study, Enhancement) | 14 | 3 | 42 |
| 3 | Presentation and Seminar Preparation | 0 | 0 | 0 |
| 4 | Web Research, Library and Archival Work | 0 | 0 | 0 |
| 5 | Document/Information Listing | 0 | 0 | 0 |
| 6 | Workshop | 0 | 0 | 0 |
| 7 | Preparation for Midterm Exam | 1 | 10 | 10 |
| 8 | Midterm Exam | 1 | 2 | 2 |
| 9 | Quiz | 0 | 0 | 0 |
| 10 | Homework | 0 | 0 | 0 |
| 11 | Midterm Project | 0 | 0 | 0 |
| 12 | Midterm Exercise | 0 | 0 | 0 |
| 13 | Final Project | 0 | 0 | 0 |
| 14 | Final Exercise | 0 | 0 | 0 |
| 15 | Preparation for Final Exam | 1 | 20 | 20 |
| 16 | Final Exam | 1 | 25 | 25 |
| 141 | ||||