What is so negative about negative binomial distribution?

Answer 1

Nothing really. It concerns an experiment with identified success and failure probabilities (p and q), or Bernoulli trials, like the conventional binomial distribution. In an negative binomial experiment, the experiment is stopped after "r" successes occur in n trials. Thus, there must be r-1 successes in the first n-1 trials, and the final trial must be a success. This stopping event causes a n-1 and r-1 terms to appear in the factorial expressions of the distribution, which I suspect is the origins of calling this distribution a "negative binomial distribution." I would prefer to call this a Bernoulli experiment distibution with a stopping rule, but that's probably much too long. Some excellent websites provide examples and more discussion: http://mathworld.wolfram.com/NegativeBinomialDistribution.html http://stattrek.com/Lesson2/NegBinomial.aspx http://en.wikipedia.org/wiki/Negative_binomial_distribution Stattrek has very good examples. Note the distribution can be expressed in a number of forms.