The negative binomial distribution models the number of trials needed to achieve a fixed number of successes in a sequence of independent Bernoulli trials. It's particularly useful in situations where you want to count the trials until a certain number of successes occurs, making it distinct from other distributions like the binomial distribution, which counts the number of successes in a fixed number of trials. This distribution is characterized by its two parameters: the number of successes required and the probability of success in each trial.
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