Binomial Distribution

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Related to Bernoulli distribution: binomial distribution, Bernoulli Principle

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 ?
Based on the feature of the Bernoulli distribution, for above system, we can get the conclusion as follows:
(18) The Bernoulli distribution approaches the Gaussian (normal or bell shaped) distribution, as the number of trials tends to infinity.
First, suppose that rather than a Bernoulli distribution, [pi] is the distribution of a bi-infinite Markov chain with memory m, given by the transition probabilities P(au, ub) for every a, b [member of] S and u [member of] [S.sup.m-1].
It turns out that the above correspondence between conserved quantities and stationary Bernoulli distributions generalizes to any number of dimensions.
If there are no multiple admissions, the Bernoulli distribution is applicable.
where the subscript B in [X.sub.B.sup.2] indicates that this formula is appropriate for data with a Bernoulli distribution. The value calculated from this formula can then be compared to a chi-square distribution with J-1 degrees of freedom in order to test [H.sub.0].
The probability that the surviving cells will undergo one cell division between two consecutive fractions is also sampled from a Bernoulli distribution with the probability of a cell to divide given by (6).
Random packet dropout in controller-actuator channel is subject to Bernoulli distribution of expected value [gamma](1 means transmission success while 0 means transmission failure).
Appendices on relative entropy in Bernoulli distributions and relative entropy and ROC curves also are included, as are a glossary and references.
TORRANO, Moments of infinite convolutions of symmetric bernoulli distributions, J.