A binomial distribution is a discrete probability distribution of the number of successful outcomes that could occur in a set number of trials with an equal chance of success. The binomial distribution is associated with the binomial experiment, which consists of four properties: a sequence ofnidentical trials, the trial outcome is either a success or failure, the probability of success or failure does not change from trial to trial, and the trial is independent (Anderson et al., 2020). In a binomial distribution, the likelihood of performing the same number of trials repeatedly is examined. My industry is in healthcare, specifically in the pharmacy department. The binomial distribution can be used to model the probability of patients that will experience side effects as a result of taking a new medication.

A Poisson distribution is a type of probability distribution that displays the likelihood that an event will occurxtimes over a certain period of time or place (Anderson et al., 2020). All events must be independent of one another, the rate at which they occur must be consistent across time, no two events may occur at once, and the mean and variance must be equal in order for the Poisson distribution to be accurate (Hayes, 2022). Poisson distribution provides the number of independent events that happen randomly over a specified period. An example of Poisson distribution is used in call centers when determining how many call center representatives to keep on staff based on the number of expected calls per hour they receive. Please discuss with reference