Course Learning Outcomes:
At the end of the course, student must be able to
(1) use applied probability theory in measuring the performance of a system.
(2) Understand statistics and data presentation.
(3) Practice performance evaluation techniques and performance measures or metrics.
(4) Summarize and analyze experiments outcomes.
(5) Compare systems using sample data.
(6) Use Queuing theory to measure performances of systems.
(7) Analyze single queue systems.
(8) Analyze simple queuing networks.
(9) Model communication networks and I/O computer systems
Relationship of Course to Program Outcomes
The course has been designed to contribute to the following program outcomes:
a) apply knowledge of mathematics, science, and engineering.
e) identify, formulate, and solve engineering problems.
k) use the techniques, skills, and modern engineering tools necessary for engineering practice.
l) knowledge of probability and statistics, mathematics through differential and integral calculus, discrete mathematics, basic sciences, and computer science.
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