ECTS - Probability and Random Processes

Probability and Random Processes (EE213) Course Detail

Course Name Course Code Season Lecture Hours Application Hours Lab Hours Credit ECTS
Probability and Random Processes EE213 3 0 0 3 7
Pre-requisite Course(s)
MATH 158
Course Language English
Course Type N/A
Course Level Bachelor’s Degree (First Cycle)
Mode of Delivery Mix
Learning and Teaching Strategies Lecture, Question and Answer, Drill and Practice, Problem Solving, Team/Group.
Course Coordinator
Course Lecturer(s)
  • Assoc. Prof. Dr. Yaser DALVEREN
Course Assistants
Course Objectives Understanding the probability axioms. Describing the discrete and continuous random variables, respectively. Distinguishing the discrete and continuous Random variables. Understanding the probability mass function (PMF), probability distribution function (PDF), cumulative distribution function (CDF), expected value, variance and standard deviation, and Gaussian random variable concepts. Defining the multiple random variables for both discrete and continuous cases. Understanding joint PMF, PDF, CDF and conditional PMF, PDF, CDF. Identifying the Stochastic Process, Poisson process, Stationary process, expected value and correlation. Describing the sum of random variables. Identifying random signal processing and cross correlation.
Course Learning Outcomes The students who succeeded in this course;
  • Understand probability axioms
  • Distinguish discrete and continuous Random variables, and describe them
  • Understand basic probability functions and concepts (mass, density and distribution functions, mean value, variance, standard deviation)
  • Describe sum of random variables
  • Define multiple random variables for both discrete and continuous cases
  • Understand joint and conditional probability concepts
  • Identify stochastic(random) process, specifially, stationary process and correlation concepts
  • Understand random signal processing and cross correlation concepts
Course Content Probability and its axioms, conditional probability, independence, counting, discrete and continuous random variables and distributions, functions of random variables, expectations, order statistics, central limit theorem, estimation of random variables, random processes and their characterization, autocorrelation function, response of linear sys

Weekly Subjects and Releated Preparation Studies

Week Subjects Preparation
1 Introduction: probability theory Study lecture notes
2 Experiments, Models, and Probabilities-1 Study lecture notes
3 Experiments, Models, and Probabilities-2 Study lecture notes
4 Sequential Experiments Study lecture notes
5 Discrete Random Variables Study lecture notes
6 Continuous Random Variables Study lecture notes
7 Probability Models of Derived Random Variables Study lecture notes
8 Conditional Probability Models-1 Study lecture notes
9 Conditional Probability Models-2 Study lecture notes
10 Midterm examination Study lecture notes
11 Multiple random variables Study lecture notes
12 Sums of Random Variables Study lecture notes
13 Stochastic Processes-1 Study lecture notes
14 Stochastic processes-2 Study lecture notes
15 Reviews Study lecture notes
16 Preparation for final examination Study lecture notes


Course Book 1. Yates, R.D., Goodman, D.J., Probability and Stochastic Processes, John Wiley Sons, 1st,2nd or 3rd edition.
Other Sources 2. Bertsekas, D.P., Tsitsiklis, J.N., Introduction to Probability, Athena Scientific, 2nd edition, 2008.
3. Leon-Garcia, L., Probability, Statistics and Random Processes for Electrical Engineering, Pearson Education, 2nd edition,2008.

Evaluation System

Requirements Number Percentage of Grade
Attendance/Participation - -
Laboratory - -
Application - -
Field Work - -
Special Course Internship - -
Quizzes/Studio Critics 8 55
Homework Assignments - -
Presentation - -
Project - -
Report - -
Seminar - -
Midterms Exams/Midterms Jury 1 20
Final Exam/Final Jury 1 25
Toplam 10 100
Percentage of Semester Work
Percentage of Final Work 100
Total 100

Course Category

Core Courses X
Major Area Courses
Supportive Courses
Media and Managment Skills Courses
Transferable Skill Courses

The Relation Between Course Learning Competencies and Program Qualifications

# Program Qualifications / Competencies Level of Contribution
1 2 3 4 5
1 Adequate knowledge of subjects related to mathematics, natural sciences, and Electrical and Electronics Engineering discipline; ability to apply theoretical and applied knowledge in those fields to the solution of complex engineering problems. X
2 An ability to identify, formulate, and solve complex engineering problems, ability to choose and apply appropriate models and analysis methods for this. X
3 An ability to design a system, component, or process under realistic constraints to meet desired needs, and ability to apply modern design approaches for this.
4 The ability to select and use the necessary modern techniques and tools for the analysis and solution of complex problems encountered in engineering applications; the ability to use information technologies effectively
5 Ability to design and conduct experiments, collect data, analyze and interpret results for investigating complex engineering problems or discipline-specific research topics.
6 An ability to function on multi-disciplinary teams, and ability of individual working.
7 Ability to communicate effectively orally and in writing; knowledge of at least one foreign language; active report writing and understanding written reports, preparing design and production reports, the ability to make effective presentation the ability to give and receive clear and understandable instructions.
8 Awareness of the necessity of lifelong learning; the ability to access knowledge, follow the developments in science and technology and continuously stay updated.
9 Acting compliant with ethical principles, professional and ethical responsibility, and knowledge of standards used in engineering applications.
10 Knowledge about professional activities in business, such as project management, risk management, and change management awareness of entrepreneurship and innovation; knowledge about sustainable development.
11 Knowledge about the impacts of engineering practices in universal and societal dimensions on health, environment, and safety. the problems of the current age reflected in the field of engineering; awareness of the legal consequences of engineering solutions.

ECTS/Workload Table

Activities Number Duration (Hours) Total Workload
Course Hours (Including Exam Week: 16 x Total Hours) 16 3 48
Special Course Internship
Field Work
Study Hours Out of Class 16 4 64
Presentation/Seminar Prepration
Homework Assignments
Quizzes/Studio Critics 8 5 40
Prepration of Midterm Exams/Midterm Jury 1 12 12
Prepration of Final Exams/Final Jury 1 12 12
Total Workload 176