Reference book:
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<br>1. Barry L. Nelson, Stochastic Modeling, McGraw-Hill International Editions, 1995.
<br>2. Law and Kelton, Simulation Modeling and Analysis, McGraw-Hill, 1982.
<br>3. Lewis and Orav, Simulation Methodology for Statisticians, Operations Analysis, and Engineers,
<br>V.1, Wadsworth and Brooks/Cole, 1989.
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<br>The course will be taught primarily from CLASS NOTES.
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<br>Prerequisites: 
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<br>Probability at the level of IE 203, statistics at the level of IE 204, computer programming at the level of IE 201. IE 512, Systems Simulation, is not a prerequisite.
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<br>Content: 
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<br>IE 5141 focuses on probabilistic and statistical methods useful to the simulation practitioner.
<br>In particular, IE 5141 focuses on input modeling, U(0,1) random numbers, random variate generation, output analysis, and variance reduction ideas. In addition to stochastic systems, Monte Carlo methods for analyzing deterministic problems (i.e., evaluating integrals) will also be considered.
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<br>Computers: Programming assignments may be done in the language of the student’s choice,probably Fortran or C.
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<br>Grading:
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<br>Home Work 20%
<br>Quiz 20%
<br>Mid-Term Exam. 20%
<br>Projects 30%
<br>Discussion 10%
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