TYPE OF COURSE UNIT	Compulsory Course
LEVEL OF COURSE UNIT	Bachelor's Degree
YEAR OF STUDY	3
SEMESTER	Fifth Term (Fall)
NUMBER OF ECTS CREDITS ALLOCATED	5
NAME OF LECTURER(S)	Assistant Professor Elmas Burcu Mamak Ekinci
LEARNING OUTCOMES OF THE COURSE UNIT	At the end of this course, the students; 1) Learn the basic concepts of probability. 2) Learn the basic concepts of continuous and discrete random variables. 3) Understand the Functions of Continuous and Discrete Probability Random Variables. 4) Learn the find of the expected value and variance of the random variables. 5) Learn the find the new probability distribution is defined as function of one or two random variable. 6) Learn and to classify of random processes.
MODE OF DELIVERY	Face to face
PRE-REQUISITES OF THE COURSE	No
RECOMMENDED OPTIONAL PROGRAMME COMPONENT	It is recommended for the student to take MAT 222 Differential Equations course before.
COURSE DEFINITION	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
RECOMENDED 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 WORKLOAD	Activities Number Hours Workload 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 Workload 150 Total Workload / 30 5 ECTS Credits of the Course 5
LANGUAGE OF INSTRUCTION	English
WORK PLACEMENT(S)	No