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We calculated confidence intervals for each of these proportions by approximating the binomial distribution with a normal distribution.
By approximating the binomial distribution with a Poisson distribution and recalling that the sum of independent Poisson random variables is also a Poisson random variable, it is straightforward to show that the method for generating the count c i specified by eqs.
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The calculation of a binomial confidence interval relies on approximating the binomial distribution with a normal distribution.
In the texture-mapping procedure, we begin by approximating the target surface with an approximating cylinder.
This follows a hypergeometric distribution which approximates the binomial distribution when n/ N HG is small n/ N HG<20.
For each window, the probability to observe ≥ k phage defense genes by chance was approximated using the binomial distribution: The results obtained for multiple windows were combined using the Bailey and Gribskov's variant of the Fisher Omnibus test [ 63].
De Moivre's most notable achievement in probability was the discovery of the first instance of central limit theorem, by which he was able to approximate the binomial distribution with the normal distribution.
Whether one uses the binomial, multiple Bernoulli or hyper-geometric models, or the empirical data, in the end, the Tanimoto score distribution can be approximated by the distribution of the ratio-of-correlated Gaussians approximating the numerator and the denominator, respectively.
Approximating the color is fine.
The number of mutations carried by a newborn can thus be approximated by a binomial random variable, taking the success probability to be 0.5 and the number of trials to be the total number of mutations in the two parents.
It has been shown that pooled sequencing is well approximated by binomial sampling [ 12].
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