ISE 5210 - Engineering Probability

• Apply Monte Carlo simulation for decision making.
• Apply Monte Carlo simulation in risk analysis.
• Apply queuing model equations to estimate performance of industrial processes.
• Apply random number generation for IE models in spreadsheet software.
• Describe Monte Carlo method for decision making.
• Describe random number generation methods.
• Describe the parameters and the application of common continuous probability distributions.
• Describe the parameters and the application of common discrete probability distributions.
• Determine the expected values and variation from combinations of independent random variables.
• Determine variance and covariance from probability functions.
• Develop markov chain model for decisions.
• Develop markov chain model for industrial processes.
• Test sample data against a hypothesized distribution using a ÷2 goodness-of-fit test.
• Use probability functions and cumulative distributions for discrete and continuous single and joint variables {f(x) and f(x,y)}.