A Poisson process is a statistical model that describes events occurring randomly over a fixed period of time or space. It is characterized by the number of events happening in non-overlapping intervals being independent and following a Poisson distribution. This means that the average rate of occurrence is constant, making it useful for modeling scenarios like phone call arrivals at a call center or the occurrence of natural disasters. In a Poisson process, the key parameters include the average rate of events, often denoted as λ (lambda). The process assumes that events happen one at a time and that the probability of more than one event occurring in an infinitesimally small interval is negligible. This framework helps in analyzing various real-world phenomena, such as traffic flow or customer arrivals in a store.