Bernoulli trials

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Bernoulli trials

[bər′nül·ē ‚trīlz]
(statistics)
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Consider a fixed number R of replicates of a truncated geometric experiment, each replicate r (1 [less than or equal to] r [less than or equal to] R) consisting of a maximum of T - 1 Bernoulli trials (with success probability [p.sub.a]) until [x.sup.(a).sub.r] = 1 successes are observed, and with the entire replicate discarded if a success has not occurred within the T - 1 trials.
Thus, each key can be viewed as an infinite sequence of Bernoulli trials. This model is often called the Bernoulli model.
In other words, the probability denoted by b(k;n,p), that n independent repeated Bernoulli trials, with probability p for success and q = 1-p for failure, will result in k successes and n-k failures (for k = 0, 1, 2, n) is called the binomial law and expressed by,
Prediction of system performance has been historically accomplished using a statistical analysis, (1) treating the combination of periodic events and the likelihood of simultaneous events as a series of Bernoulli trials. The parameters of the receiver system are analyzed with respect to the radar signal of interest and the mean time to intercept is computed.
In this paper, we assume the existence of a noise source that delivers a continuous string of random binary values, commonly called elementary Bernoulli trials (or trials, for short).
These problems are called Bernoulli trials. Bernoulli systems have two outcomes--the outcome we want or are interested in, called a success, and the other outcome, called a failure.

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