2001•Journal of Applied ProbabilityRequires access

On the nature of the binomial distribution

P. Vellaisamy, Abraham P. Punnen

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Abstract

We examine how the binomial distribution B(n,p) arises as the distribution S n = ∑ i=1 n X i of an arbitrary sequence of Bernoulli variables. It is shown that B(n,p) arises in infinitely many ways as the distribution of dependent and non-identical Bernoulli variables, and arises uniquely as that of independent Bernoulli variables. A number of illustrative examples are given. The cases B(2,p) and B(3,p) are completely analyzed to bring out some of the intrinsic properties of the binomial distribution. The conditions under which S n follows B(n,p), given that S n-1 is not necessarily a binomial variable, are investigated. Several natural characterizations of B(n,p), including one which relates the binomial distributions and the Poisson process, are also given. These results and characterizations lead to a better understanding of the nature of the binomial distribution and enhance the utility.

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What this paper is about

We examine how the binomial distribution B(n,p) arises as the distribution S n = ∑ i=1 n X i of an arbitrary sequence of Bernoulli variables. It is shown that B(n,p) arises in infinitely many ways as the distribution of dependent and non-identical Bernoulli variables, and arises uniquely as that of independent Bernoulli variables. A number of illustrative examples are given. The cases B(2,p) and B(3,p) are completely analyzed to bring out some of the intrinsic properties of the binomial distribution. The conditions under which S n follows B(n,p), given that S n-1 is not necessarily a binomial variable, are investigated. Several natural characterizations of B(n,p), including one which relates the binomial distributions and the Poisson process, are also given. These results and characterizations lead to a better understanding of the nature of the binomial distribution and enhance the utility.

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Available abstract

We examine how the binomial distribution B(n,p) arises as the distribution S n = ∑ i=1 n X i of an arbitrary sequence of Bernoulli variables. It is shown that B(n,p) arises in infinitely many ways as the distribution of dependent and non-identical Bernoulli variables, and arises uniquely as that of independent Bernoulli variables. A number of illustrative examples are given. The cases B(2,p) and B(3,p) are completely analyzed to bring out some of the intrinsic properties of the binomial distribution. The conditions under which S n follows B(n,p), given that S n-1 is not necessarily a binomial variable, are investigated. Several natural characterizations of B(n,p), including one which relates the binomial distributions and the Poisson process, are also given. These results and characterizations lead to a better understanding of the nature of the binomial distribution and enhance the utility.

Key concepts: Mathematics, Binomial distribution, Negative binomial distribution, Bernoulli distribution, Beta negative binomial distribution, Poisson binomial distribution, Beta-binomial distribution, Bernoulli's principle

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