# Department of Electrical and Electronics Engineering

Course Details

#### ELE709 - Probability Theory and Stochastic Processes

2022-2023 Fall term information
The course is open this term
Supervisor(s)
Name Surname Position Section
Prof.Dr. Berkan Dülek Supervisor 1
Weekly Schedule by Sections
Section Day, Hours, Place
All sections Friday, 09:00 - 11:45, SS

Timing data are obtained using weekly schedule program tables. To make sure whether the course is cancelled or time-shifted for a specific week one should consult the supervisor and/or follow the announcements.

ELE709 - Probability Theory and Stochastic Processes
 Program Theoretıcal hours Practical hours Local credit ECTS credit PhD 3 0 3 10
 Obligation : Elective Prerequisite courses : - Concurrent courses : - Delivery modes : Face-to-Face Learning and teaching strategies : Lecture, Question and Answer, Problem Solving Course objective : After introducing the basic concepts of the probability theory in the undergraduate study, in this course the theory is presented with sufficient elaboration supported with many engineering oriented examples. With this it is aimed to have the students build a solid understanding of the concepts and establish an ability to solve the problems by using these concepts as a tool. Learning outcomes : Knows the basic components of probability model. Knows how to model the sample space in an experiment Computes the statistical properties (mean, variance, covariance, correlation) of a given one/multi variable random variable(s). Have the knowledge to follow and understand the advanced and complex probability theory related concepts. In engineering problems recognizes the random phenomena and applies the correct statistical models. Course content : The Axioms of Probability, Probability Space Conditional probability, Bernoulli trials The Concept of a Random Variable Distribution and density functions, Conditional distributions Asymptotic approximations for binomial random variables Functions of one random variable, Transformation of a random variable Mean and Variance Concepts, Moments, Characteristic Functions Two random variables, Bivariate distributions One function of two random variables Two functions of two random variables (Jacobian matrix) Joint Moments, Joint Characteristic Functions, Conditional Bivariate Distributions Random Processes, Wide Sense and Complete Stationarity, Statistical averages and ergodicity Autocorrelation and cross-correlation functions, Gauss processes References : Papoulis and Pillai, Probability, Random Variables, and Stochastic Processes, ; 4th Ed., Mc-Graw Hill, 2002.; Milton and Arnold, Introduction To Probability and Statistics, 4th Ed., ; Mc-Graw Hill, 2003.
Course Outline Weekly
Weeks Topics
1 The Axioms of Probability, Sample Space, Conditional Probability
2 Independence, Bernoulli Trials
3 Random Variable Concept
4 Distribution and Density Functions, Conditional Distributions
5 Asymptotic Approximations for Binomial Random Variables
6 Functions of One Random Variable, Transformation of a Random Variable
7 Mean and Variance Concepts, Moments, Characteristic Functions
8 Midterm Exam
9 Two Random Variables, Bivariate Distributions
10 One Function of Two Random Variables
11 Two Functions of Two Random Variables (Jacobian Matrix)
12 Joint Moments, Joint Characteristic Functions, Conditional Bivariate Distributions
13 Random Processes and their properties, Stationarity, Statistical averages and ergodicity
14 Autocorrelation and cross-correlation functions, Gauss processes
15 Preparation Week for Final Exams
16 Final exam
Assessment Methods
Course activities Number Percentage
Attendance 0 0
Laboratory 0 0
Application 0 0
Field activities 0 0
Specific practical training 0 0
Assignments 0 0
Presentation 0 0
Project 0 0
Seminar 0 0
Quiz 0 0
Midterms 1 50
Final exam 1 50
Total 100
Percentage of semester activities contributing grade success 50
Percentage of final exam contributing grade success 50
Total 100
Course activities Number Duration (hours) Total workload
Course Duration 14 3 42
Laboratory 0 0 0
Application 0 0 0
Specific practical training 0 0 0
Field activities 0 0 0
Study Hours Out of Class (Preliminary work, reinforcement, etc.) 14 11 154
Presentation / Seminar Preparation 0 0 0
Project 0 0 0
Homework assignment 0 0 0
Quiz 0 0 0
Midterms (Study duration) 1 50 50
Final Exam (Study duration) 1 54 54