In my area of interest, which is small business operations, specifically in a bakery environment, a great example of a Poisson experiment is the arrival of customers over a fixed time period. Let's explore this scenario in detail and see how it aligns with the characteristics of a Poisson distribution. Characteristics of the Poisson Experiment 1. Number of Events in a Fixed Interval: At a bakery, the number of customer arrivals can be observed within a fixed interval of time, such as an hour or a day. For example, we might measure how many customers enter the bakery between 8:00 AM and 9:00 AM on a typical weekday. 2. Known Average Rate: There is a known average rate at which customers arrive at the bakery. This could be based on historical data, such as observing that on average, 30 customers come into the bakery every hour during the morning rush. 3. Independence of Events: The arrival of one customer is independent of the time since the last customer arrived. In other words, the fact that a customer just walked in does not make it more or less likely that another customer will arrive in the next few minutes. Each customer's