Compute the probability mass function (PMF) for the binomial distribution, given the number of trials, the number of successes, and the probability of observing a successful outcome. The binomial distribution PMF identifies the likelihood that an associated discrete random variable will have an exact value, and is very useful for analytics studies that rely on binomial experiments and probabilities.
Compute the probability mass function (PMF) for the Poisson distribution, given the expected number of event occurrences and the observed number of event occurrences. The Poisson distribution PMF identifies the likelihood that an associated discrete random variable will have an exact value, and is very useful for analytics studies that involve Poisson probabilities.