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The Bernoulli distribution is a special case of the binomial distribution with = [4] The kurtosis goes to infinity for high and low values of p , {\displaystyle p,} but for p = 1 / 2 {\displaystyle p=1/2} the two-point distributions including the Bernoulli distribution have a lower excess kurtosis , namely −2, than any other probability ...
SolverStudio is a free Excel plug-in developed at the University of Auckland [1] that supports optimization and simulation modelling in a spreadsheet using an algebraic modeling language. It is popular in education, [ 2 ] the public sector [ 3 ] and industry for optimization users because it uses industry-standard modelling languages and is ...
A CAS designed for the solution of problems in physical field theory. An unpublished computational program written in Pascal called Abra inspired this open-source software. Abra was originally designed for physicists to compute problems present in quantum mechanics.
A Bernoulli process is a finite or infinite sequence of independent random variables X 1, X 2, X 3, ..., such that for each i, the value of X i is either 0 or 1; for all values of , the probability p that X i = 1 is the same. In other words, a Bernoulli process is a sequence of independent identically distributed Bernoulli trials.
The following theorem presents a strengthened version of the Bernoulli inequality, incorporating additional terms to refine the estimate under specific conditions. Let the expoent r {\displaystyle r} be a nonnegative integer and let x {\displaystyle x} be a real number with x ≥ − 2 {\displaystyle x\geq -2} if r {\displaystyle r} is odd and ...
The probability density function (PDF) for the Wilson score interval, plus PDF s at interval bounds. Tail areas are equal. Since the interval is derived by solving from the normal approximation to the binomial, the Wilson score interval ( , + ) has the property of being guaranteed to obtain the same result as the equivalent z-test or chi-squared test.
In particular, there is a systematic methodology to solve the numerical coefficients {(a n,b n)} N n = 1 that yield a minimax approximation or bound for the closely related Q-function : Q ( x ) ≈ Q̃ ( x ) , Q ( x ) ≤ Q̃ ( x ) , or Q ( x ) ≥ Q̃ ( x ) for x ≥ 0 .
A random variable X has a Bernoulli distribution if Pr(X = 1) = p and Pr(X = 0) = 1 − p for some p ∈ (0, 1).. De Finetti's theorem states that the probability distribution of any infinite exchangeable sequence of Bernoulli random variables is a "mixture" of the probability distributions of independent and identically distributed sequences of Bernoulli random variables.