Izlence

Course Code & Number:

EE 304

Course Title:

Probability and Random Variables

Level:

BS

Credit Hours/ ECTS Credits:

(3+0+0) 3 TEDU Credits, 5 ECTS Credits

Academic Year

2019

Semester

Spring

Catalog Description:

Experiments, models, and probabilities. Sequential experiments. Discrete random variables. Continuous random variables. Multiple random variables. Independence of random variables. Correlation. Covariance. Derived random variables. Distributions of functions of random variables. Conditional probability models. Conditioning random variables by an event. Conditioning by a random variable. Iterated expectation.

Pre-requisite / Co-requisite:

Instructor:

Hüseyin Uğur Yıldız

Syllabus File:

s1819_syllabus_ee304.pdf

Sap Event ID:

50104169

Office Hours:

Wednesday (16.00 –18.00) (or by appointment)

Teaching Assistant(s):

N/A

Required Reading:

R. D. Yates and D. J. Goodman, “Probability and Stochastic Processes: A Friendly Introduction for Electrical and Computer Engineers”, 3rd Edition International Student Version, Wiley, 2014.

Suggested / Recommended Reading:

• A. Leon-Garcia, “Probability, Statistics, and Random Processes For Electrical Engineering”, Prentice Hall, 3rd Edition, 2008.
• D. P. Bertsekas and J. N. Tsitsiklis, "Introduction to Probability", 2nd Edition, Athena Scientific, 2002.

Learning Outcomes:

Upon successful completion of this course, students will be able to:
(1) Explain the basic probability theory concepts, including random experiments, axioms, conditional probability, and independence,
(2) Express probability mass function (PMF), cumulative distribution function (CDF), expected value, and variance for discrete random variables,
(3) Use probability density function (PDF) and CDF to investigate continuous random variables,
(4) Analyze joint probability distributions of multiple random variables, marginal distributions, correlation, and covariance,
(5) Evaluate the probability distribution of a function of random variables,
(6) Formulate conditional probability distribution functions for discrete and continuous random variables.

Software Usage:

MATLAB with Communications System Toolbox
https://www.mathworks.com/products/communications.html

Learning Activities and Teaching Methods:

Assessment Methods and Criteria:

Student Workload:

Assessment Methods and Criteria Others:

Active Learning Exercises

Assignments / Grading:

1.  Midterm Exams [50%]: There will be two closed-book & closed-note midterm exams, 25% for each exam. Exam 1 and 2 will be on the 5th and 9th weeks, respectively. Date and time of the midterm exams will be announced later.
2. Final [40%]: There will be a cumulative closed-book & closed-note final exam covering all topics. Date and time of the final exam will be announced at the end of the semester.
3. Active Learning Exercises [10%]: There will be 5 closed-book Active Learning Exercises (ALEs) which will be performed as collaborative quizzes (2% for each quiz). In the first lecture of the ALE week, a group of 2 students gets a 2-question practice quiz to complete as a team. Each group needs to answer only one of the given questions. In the second lecture of the ALE week, a similar 2-question is divided into 2-separate slips paper with one question each. Each group member completes one slip individually. The two ALE scores are combined with the individual score counting for 60% and the group quiz counting for 40% of the grade.

Attendance:

Not required