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Nov 23, 2024
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ISE 3210 - Engineering Probability
Introduction to probability, concept of random variables, discrete and continuous probability distributions, and expectation.
Requisites: MATH 2302 and C- or better in ET2450 and WARNING: No credit for both this course and the following (always deduct credit for first course taken): MATH 3500. No credit if taken after EE 3713
Credit Hours: 3
Repeat/Retake Information: May be retaken two times excluding withdrawals, but only last course taken counts.
Lecture/Lab Hours: 3.0 lecture
Grades: Eligible Grades: A-F,WP,WF,WN,FN,AU,I
Learning Outcomes: - Students will be able to describe and apply Monte Carlo simulation for decision making and risk analysis.
- Students will be able to describe and apply common discrete and continuous probability distributions.
- Students will be able to apply queuing model equations to evaluate performance of industrial processes.
- Students will be able to analyze Markov chain models for decisions.
- Students will be able to recognize, evaluate, and connect ethical issues.
- Students will be able to apply ethical perspectives, theories, or concepts to a decision-making situation.
- Students will be able to evaluate alternative ethical perspectives within a decision-making situation.
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