| Course Type | Compulsory Course |
|---|
| Course Level | Bachelor's Degree |
|---|
| Year of Study | 3 |
|---|
| Semester | Fifth Term (Fall) |
|---|
| ECTS | 5 |
|---|
| Name of Lecturer(s) |
|
| Learning Outcomes |
At the end of this course, the students;
- Learn the basic concepts of probability.
- Learn the basic concepts of continuous and discrete random variables.
- Understand the Functions of Continuous and Discrete Probability Random Variables.
- Learn the find of the expected value and variance of the random variables.
- Learn the find the new probability distribution is defined as function of one or two random variable.
- Learn and to classify of random processes.
|
| Mode of Delivery | Face to face |
|---|
| Prerequisites | No |
|---|
| Recommended Optional Programme Components | It is recommended for the student to take MAT 222 Differential Equations course before. |
|---|
| Course Description | In this course, basic principles of probability, definition and basic theorems of probability, concept of a random variable, probability distributions, mathematical expectation, moments, some discrete and continuous distributions, transformations of a random variable, joint probability distributions, transformations of multiple random variables are discussed. Then, in the processes part of the course, the random process concept, classification of processes stationarity and independence, correlation functions, Gaussian random processes, Poisson random processes and spectral characteristics of random processes are studied. |
|---|
| Course Contents |
| WEEK |
TOPICS |
|
1st Week |
Basic Concepts of Probability |
|
2nd Week |
Definition of probability, conditional probability, Bayes' Theorem and Independent Events |
|
3rd Week |
Concept of Random Variable, Discrete and Continuous Random Variables |
|
4th Week |
Probability Functions of Random Variables |
|
5th Week |
Joint Probability Distributions, Statistical Independence |
|
6th Week |
Mathematical Expected Value and Variance |
|
7th Week |
Special Continuous and Discrete Distributions |
|
8th Week |
Midterm Exam |
|
9th Week |
Transformations of Random Variables |
|
10th Week |
Probability Distributions for One or Two Random Variable Function |
|
11th Week |
Random Process Concept, Classification of Processes |
|
12th Week |
Stationarity and Independence |
|
13th Week |
Correlation Functions |
|
14th Week |
Gaussian and Poisson Stochastic Processes |
|
| Recommended or Required Reading | Peebles, Peyton Jr. Probability and Random Variables and Random Signal Principles Mc-Graw Hill.
Walpole, Ronald E. Myers, Raymond H.; Myers, Sharon L. "Probability and Statistics for Engineers and Scientists, Prentice-Hall, (1998).
Leon-Garcia A., Probability and Random Processes for Electrical Engineering, Second Edition, Addison Wesley, (1994)
|
|---|
| Planned Learning Activities and Teaching Methods |
- Lecture
- Questions/Answers
|
|---|
| Assessment Methods and Criteria |
|
Quantity |
Percentage (%) |
| Mid-term |
1 |
30 |
| Assignment |
1 |
10 |
| Quiz |
2 |
20 |
| Attendance |
1 |
5 |
| Total(%) |
|
65 |
| Contribution of In-term Studies to Overall Grade(%) |
|
65 |
| Contribution of Final Examination to Overall Grade(%) |
|
35 |
| Total(%) |
|
100 |
|
| ECTS Allocated Based on Student Workload |
| Activities |
Quantity |
Duration (Hour) |
Total Workload (Hour) |
| Midterm exam |
1 |
2 |
2 |
| Preparation for Quiz |
2 |
4 |
8 |
| Individual or group work |
13 |
4 |
52 |
| Preparation for Final exam |
1 |
16 |
16 |
| Course hours |
14 |
4 |
56 |
| Preparation for Midterm exam |
1 |
12 |
12 |
| Laboratory (including preparation) |
0 |
0 |
0 |
| Final exam |
1 |
2 |
2 |
| Homework |
0 |
0 |
0 |
| Quiz |
2 |
1 |
2 |
| Total Work Load | 150 |
| Total Work Load / 30 (h) | 5 |
| ECTS Credit of the Course | 5 |
|
| Language of Instruction | English |
|---|
| Work Placement(s) | No |
|---|
