As an example of a Poisson experiment, I'll be using my wife's family business with the number of customers visiting their vegetable stall during a specific time period. We want to find out and analyze the number of customers visiting the stall between 8 am and 9 am each day.Number of events occurring in a fixed interval of time: In our case, the event in our experiment would be the customers visiting the vegetable stall during the one-hour time frame of 8-9 am.Known average rate: We'll be able to determine the average rate of customers visiting by collecting data over a set time period. As an example, if we were to observe that on average 10 customers visited per hour during this period between 8-9 am, we're able to then use this as the known average rate. Independence of events: Having one customer visit the stall, does not in any way, affect the visiting of another or anyone else visiting. Each customer's visit is independent of the time and visit of the previous customer visited.My vegetable stall example meets all the characteristics of a Poisson experiment. We're able to use the Poisson distribution to then analyze these figures, and the probability of a specific number of customers visiting during the given time of 8 - 9 am.Under certain conditions, the Poisson distribution can also be used to help with an approximation of a binomial distribution. comment please