In probability theory and statistics, the Poisson distribution, named after French mathematician Denis Poisson, is a discrete probability distribution that expresses the probability of a given number of events occurring in the rationale of a fixed interval of time or space if these events occur with a known constant mean rate and independently of the time since the last event. The Poisson distribution can also be used for the number of events in other specified intervals such as distance, area or volume. A more simplified definition can be that it is a probability function that is used for charts for defects.
For instance, a call center receives an average of 180 calls per hour, 24 hours a day. The calls are independent; receiving one does not change the probability of when the next one will arrive. The number of calls received during any minute has a Poisson probability distribution: the most likely numbers are 2 and 3 but 1 and 4 are also likely and there is a small probability of it being as low as zero and a very small probability it could be 10. Another example is the number of decay events that occur from a radioactive source during a defined observation period.
Wikipedia. Poisson distribution. https://en.wikipedia.org/wiki/Poisson_distribution