IND 3820 - Stochastic Processes

• Application of probability and statistics to engineering problems
• Make difficult decisions using systematic decision-making processes
• Develop and use queueing theory single server Markovian systems
• Use queueing theory for multi-server systems with complex distributions
• Develop systems models and recommend improvements based on the stochastic analysis of the system
• Develop an understanding of how the stochastic nature of systems impact business and industry

• Process modelling
• Probability theory
• Conditional probabilities
• Probability distribution functions for discrete random variables
• Cumulative probability distributions
• Probability density functions
• Joint probability functions
• Conditional probability and Bayesian analysis
• Binomial, normal, Poisson, and chi-squared distributions and expectations
• Inverse cumulative distribution functions

• Decision analysis
• Decision process
• Decision-making under certainty
• Decision-making under uncertainty
• Decision-making under risk
• Bayesian probability analysis
• Bernoulli processes
• Poisson processes
• Queueing theory
• Little’s law
• Markovian analysis
• Dynamic network optimization
• Game theory