| 11. | *In Statistics, the limiting case of Binomial distribution is Poisson distribution.
|
| 12. | The answer can be traced back to the normal approximation to the binomial distribution.
|
| 13. | Observe that the pdf is the Beta-binomial distribution when K = 2.
|
| 14. | In a binomial distribution, the theoretical variance is
|
| 15. | The beta-binomial distribution is a good example of how this process works.
|
| 16. | The Bernoulli distribution is a special case of the binomial distribution with n = 1.
|
| 17. | In discrete terms, the number of overestimates minus underestimates will have a binomial distribution.
|
| 18. | This statistic will have a binomial distribution ( assuming results of trials are idependent ).
|
| 19. | The distribution of is the binomial distribution.
|
| 20. | One way to generate random samples from a binomial distribution is to use an inversion algorithm.
|
