Binomial Distribution


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Related to Binomial Distribution: Poisson distribution, normal distribution

Binomial Distribution

The distribution of successes and failures of a certain number of Bernoulli trials. A Bernoulli trial is a test in which there are precisely two random outcomes: success and failure. For example, if one is testing whether flipping a coin will result in heads, the two outcomes are yes (success) or no (failure). A binomial distribution, then, would be the number of heads compared to the number of tails in a given number of flips. It is also called a Bernoulli distribution.
References in periodicals archive ?
On the distributions obtained by varying the number of trials in a binomial distribution. Annals of the Institute of Statistical Mathematics, 13(1), 47-51.
At a given variance, the binomial distribution can be approximated by the normal distribution (Bolker, 2008).
[6] suggested the modified median unbiased estimator (MMUE) in two independent binomial distributions. Let p be the estimator of success probability which satisfies
Fact 3 Let X have a binomial distribution. For any 0 [less than or equal to] [delta] [less than or equal to] 1 we have
We fit the transmission data from patients within subgroups to the negative binomial distribution with mean R and dispersion parameter k, which characterizes individual variation in transmission, including the likelihood of superspreading events (i.e., when infected persons disproportionately transmit the virus to others) (25).
The results provide an estimate of the number of funds expected to win as a result of skill using the standard binomial distribution. If fewer such funds exist than expected, perhaps because funds regularly move into and out of a winning position, then mutual fund performance cannot be distinguished from luck.
Using Monte Carlo simulation techniques, the zero-inflated binomial samples were generated while taking into account the ZIB model (RUCKSTUHL; WELSH, 2001), characterized by the mixture of two components in such a way that one component presumes that the occurrence of zero is defined by a [gamma] probability, while the other component represents a binomial distribution with a (1-[gamma]) probability.
Chance mechanisms generating the negative binomial distribution. In: Random counts in models and structures (ed.
The number of vacations follows a binomial distribution with parameters p and K.
Some other researchers who take this a step further will discuss whether negative binomial distribution or geometric distribution better fits the frequency [6].
We consider three types of service time distributions: a geometric distribution, a negative binomial distribution, and a mixture of two different geometric distributions.