People Innovation Excellence
 

STOCHASTIC PROCESS (4 Credits)

Learning Outcomes:

On successful completion of this course, student will be able to: Apply probability concept to solve Bayesian problem; Calculate the important concept of random variables with Poisson, Exponential and Gamma distributions; Calculate limiting probabilities for Discrete and Continuous Times Markov Chain in production process, birth and death process or other real phenomen; Apply the important concept of Poisson process, Interarrival and Waiting time distribution; Apply Renewal, Queuing and Reliability theory in production process and network of queues.

Topics:

  1. Probability and Random Variables;
  2. Discrete-Time Markov Chains;
  3. Poisson Process;
  4. Continuous-Time Markov Chains;
  5. Renewal Process;
  6. Queuing Theory;
  7. Reliability Theory.

Published at : Updated

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