Introduction to Bernoulli Trials

The second provides a realization from this surface in the form of a binary map yielding the results of Bernoulli trials across all locations; this surface is only partially observed.

For that reason, I calculated the potassium ions' probability to reach the proposed threshold,while also using Bernoulli trials equation to calculate the probability of action potential induction.

The traditional way of doing this applies the binomial distribution, which describes the outcome of a series of Bernoulli trials.

Consider a sequence of independent Bernoulli trials and assume that the probability (or odds) of success (or the probability (or odds) of failure) at a trial varies (increases or decreases) geometrically, with rate q, either with the number of trials or with the number of successes.

This article proposes statistical models based on dependent Bernoulli trials, along with corresponding methodology for parameter estimation.

The first model is the lattice renewal binomial censored δ shock model, in which shocks occur independently at discrete time epochs according to Bernoulli trials.

We apply this methodology to goodness of fit tests for Bernoulli trials, generated by a single distributional family, but with covariates varying over the sample.

I then build a series of simulations involving Bernoulli trials at sequences of different probabilities that incorporate either a sequential dependence mechanism, a baseline deflection mechanism, or both.

We are interested in two properties of real numbers: the first one is the property of having given digit frequencies in the binary expansion, such as the well known Besicovitch sets, and the second one is the property of having the longest run of heads in the n independent Bernoulli trials, that is the so called Erdös–Rényi sets.

To assess the quality of scenario-based solutions a posteriori, validation tests based on Bernoulli trials have been widely adopted in practice.

The probability distribution of the number of success runs of the length k (k ≥ 1) in n (n ≥ 1) Bernoulli trials is obtained.