Poisson Process
In Data Science, a Poisson Process is a stochastic process that models the occurrence of events over time. It is a counting process that assumes events occur independently and at a constant rate. The Poisson Process is characterized by the Poisson distribution, which describes the probability of a certain number of events occurring in a fixed interval of time. The Poisson Process is widely used in various fields, including telecommunications, finance, and healthcare, to model the arrival of customers, stock price movements, and disease outbreaks, respectively. In Data Science, the Poisson Process is used to model the arrival of data packets in computer networks, the number of clicks on a website, and the frequency of machine failures in a manufacturing plant.
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