•
•           Information on Degree Programmes

COURSE INFORMATON
Course Title Code Semester L+P Hour Credits ECTS
Probability and Random Variables * EEE   214 4 3 3 5

 Prerequisites and co-requisites Yok Recommended Optional Programme Components None

Language of Instruction Turkish
Course Level First Cycle Programmes (Bachelor's Degree)
Course Type
Course Coordinator Asst.Prof.Dr. Selma TOKER KUTAY
Instructors
 Dr. Öğr. Üyesi SELMA TOKER KUTAY 1. Öğretim Grup:A Dr. Öğr. Üyesi SELMA TOKER KUTAY 2. Öğretim Grup:A

Assistants
Goals
To give students knowledge of probability and random variables in order to to develop understanding for random phenomena in engineering.
Content
Basic concepts on probability and random variables, distribution functions, probability density function, probability mass function, expected value and variance, moments, bivariate distributions, marginal distributions, conditional distributions, named discrete distributions, named continuous distributions, functions of random variables

Learning Outcomes
-

Course's Contribution To Program
NoProgram Learning OutcomesContribution
12345
1
Has capability in those fields of mathematics and physics that form the foundations of engineering.
2
Grasps the main knowledge in the basic topics of electrical and electronic engineering.
3
Comprehends the functional integrity of the knowledge gathered in the fields of basic engineering and electrical-electronics engineering.
4
Identifies problems and analyzes the identified problems based on the gathered professional knowledge.
5
Formulates and solves a given theoretical problem using the knowledge of basic engineering.
X
6
Has aptitude for computer and information technologies
7
Knows English at a level adequate to comprehend the main points of a scientific text, either general or about his profession, written in English.
8
Has the ability to apply the knowledge of electrical-electronic engineering to profession-specific tools and devices.
9
Has the ability to write a computer code towards a specific purpose using a familiar programming language.
10
Has the ability to work either through a purpose oriented program or in union within a group where responsibilities are shared.
11
Has the aptitude to identify proper sources of information, reaches them and uses them efficiently.
X
12
Becomes able to communicate with other people with a proper style and uses an appropriate language.
13
Internalizes the ethical values prescribed by his profession in particular and by the professional life in general.
14
Has consciousness about the scientific, social, historical, economical and political facts of the society, world and age lived in.
X

Course Content
WeekTopicsStudy Materials _ocw_rs_drs_yontem
1 Set theory, random experiment, event Review of the tliterature
2 Counting rules, permutation,i combination Review of the previous lecture and the literature
3 Probability definitions Review of the previous lecture and the literature
4 Consequences of axiomatic probability Review of the previous lecture and the literature
5 Conditional probability, Bayes Theorem Review of the previous lecture and the literature
6 Independence of events, random variables Review of the previous lecture and the literature
7 Discrete and continuous sample spaces, distribution function Review of the previous lecture and the literature
8 Probability density function, probability mass function, bivariate distributions Review of the previous lecture and the literature
9 Midterm Exam Review of the previous lecture and the literature
10 Marginal distributions, conditional distributions Review of the previous lecture and the literature
11 Expected value, variance, moments Review of the previous lecture and the literature
12 Moment generating function, probability generating function, characteristic function Review of the previous lecture and the literature
13 Probability inequalities, approximation methods Review of the previous lecture and the literature
14 Named discrete distributions Review of the previous lecture and the literature
15 Named continuous distributions Review of the previous lecture and the literature
16-17 Functions of random variables Review of the previous lecture and the literature