Stochastic Processes

Catalog description

Countless real-world phenomena, ranging from biological population sizes and queuing times to weather parameters and stock prices, exhibit stochastic behavior. They can be effectively modeled as stochastic processes, which represent random quantities evolving over time. This course serves as an essential introduction to the theory and practical applications of stochastic processes. By emphasizing pivotal concepts, including random walks, branching processes, Markov chains, the Poisson process, and Brownian motion, it equips students with the analytical tools to comprehend and analyze diverse stochastic phenomena across engineering, economics, biology, physics and computer science.