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Information
| Code | CENG533 |
| Name | Random Variables and Processes for Computer Engineering |
| Term | 2024-2025 Academic Year |
| Term | Fall |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Yüksek Lisans Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator | Prof. Dr. MEHMET FATİH AKAY |
| Course Instructor |
Prof. Dr. MEHMET FATİH AKAY
(A Group)
(Ins. in Charge)
|
Course Goal / Objective
Introduce the student with probability concepts and their relation to the events.
Course Content
Random Variables and Processes for Computer Engineering, Probability, conditional probability, Bernoulli trials, the concept of a random variable, distribution and density functions, specific random variables, conditional distributions, functions of one random variable, mean and variance, functions of two random variables, conditional expected values, stochastic processes, systems with stochastic inputs, the power spectrum, discrete-time processes, poisson process.
Course Precondition
Basic knowledge of probability and statistics
Resources
Gallager, R. G. (2013). Stochastic processes: theory for applications. Cambridge University Press.
Notes
Ibe, O. (2014). Fundamentals of Applied Probability and Random Processes. Elsevier.
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Learn probability and conditional probability. |
| LO02 | Learn Bernoulli trials. |
| LO03 | Learn random variables and types of random variables. |
| LO04 | Learn expected value and variance |
| LO05 | Learn random functions. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. | |
| PLO02 | Bilgi - Kuramsal, Olgusal | By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. | 3 |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the new and developing practices of his / her profession and examining and learning when necessary. | |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. | 5 |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. | 3 |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. | 3 |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the skills of learning. | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. | 2 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. | 2 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. | 1 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in all professional activities. | 4 |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to probability | There is no prerequisite. | |
| 2 | Set theory and conditional probability | There is no prerequisite. | |
| 3 | Bernoulli trials | There is no prerequisite. | |
| 4 | Random variables | There is no prerequisite. | |
| 5 | Cumulative distribution function | There is no prerequisite. | |
| 6 | Probability density function | There is no prerequisite. | |
| 7 | Specific random variables | There is no prerequisite. | |
| 8 | Mid-Term Exam | There is no prerequisite. | |
| 9 | Discrete random variables | There is no prerequisite. | |
| 10 | Conditional distributions | There is no prerequisite. | |
| 11 | Asymptotic approximations | There is no prerequisite. | |
| 12 | Functions of one random variable | There is no prerequisite. | |
| 13 | Expected value | There is no prerequisite. | |
| 14 | Functions of two random variables | There is no prerequisite. | |
| 15 | Sample of Problems | There is no prerequisite. | |
| 16 | Term Exams | There is no prerequisite. | |
| 17 | Term Exams | There is no prerequisite. |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||