Sep 28, 2024  
2023-2024 Graduate Catalog 
    
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2023-2024 Graduate Catalog [ARCHIVED CATALOG]

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IE 8780 - Foundations of Probability for Industrial Engineering

3 Credits (3 Contact Hours)
This course is intended for doctoral students. The primary objective of this course is to equip industrial engineering students with the foundational tools and techniques needed to design, model and analyze stochastic systems in a variety of operational settings common to industrial engineering. Students are exposed to common mathematical proof techniques, rudimentary elements of real analysis and important measure theory concepts in preparation for more advanced probabilistic modeling concepts. Probability topics include conditional expectations and probability, Bayes’ theorem, independence, random variables, distribution functions, expectations, inequalities, transforms in stochastic modeling, convergence of random variables, limit theorems and common stochastic orders. Application areas may include manufacturing and service systems, reliability and maintenance, transportation and communications. Students are expected to have completed a course in calculus-based probability before enrolling in this course.


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