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Stochastic Modeling Assignment Help
Stochastic Modeling or stochastic process is a system of modeling that uses probability for analyzing systems that can evolve dynamically over time. It uses probability for determining factors that can influence the outcome of a process and the number of ways in which the outcome can be achieved.
Numerous examples of where stochastic modeling is used can include manufacturing processes, computer applications, communications applications, economic applications, business applications, military applications, and biological applications. Stochastic modeling also helps in simulating various outcomes so that processes can be designed to achieve desired and optimum outcomes.
Some of the topics covered under Stochastic Modeling include
- Probability Review
- Discrete Distributions
- Important Continuous Distributions
- Conditional Probability and Conditional Expectation
- Simulation
- Arrival-Counting Process
- Discrete-Time Processes and Continuous-Time Processes
- Markov Chains
- Long Run Behavior of Markov Chains
- Poisson Processes
- Continuous Time Markov Chains
- Renewal Phenomena
- Branching process and Population Growth
- Queuing Systems
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