A stochastic process is a collection of random variables that represent a system evolving over time. It is used to model situations where outcomes are uncertain and can change unpredictably, such as stock prices or weather patterns. Each random variable in the process corresponds to a specific time point, allowing for the analysis of how the system behaves over time. These processes are essential in various fields, including finance, queueing theory, and physics. They help researchers and analysts understand complex systems by providing a framework to study the probabilities of different outcomes and their potential impacts on the system's future state.