Contenuto principale

binostat

Binomial mean and variance

Description

m = binostat(n,p) returns the mean for the binomial distribution with the specified number of trials n and probability of success for each trial p.

[m,v] = binostat(n,p) also returns the variance for the distribution.

example

Examples

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Compute the mean and variance of a binomial distribution for 100 trials, where the probability of success for each trial is 5%.

n = 100;
p = 0.05;
[mean,variance] = binostat(n,p)
mean = 
5
variance = 
4.7500

Input Arguments

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Number of trials, specified as a positive integer or an array of positive integers. If both n and p are arrays, they must be the same size. If either n or p is a scalar, then binostat expands the scalar argument into a constant array of the same size as the other argument.

Data Types: single | double

Probability of success for each trial, specified as a scalar value in the interval [0 1] or an array of scalar values in the interval [0 1]. If both n and p are arrays, they must be the same size. If either n or p is a scalar, then binostat expands the scalar argument into a constant array of the same size as the other argument.

Data Types: single | double

Output Arguments

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Mean for the binomial distribution, returned as a numeric scalar or an array of numeric scalars. m is the same size as n and p. Each element in m is the mean of the binomial distribution specified by the corresponding elements in n and p.

The mean of the binomial distribution with parameters n and p is np.

Variance for the binomial distribution, returned as a numeric scalar or an array of numeric scalars. v is the same size as n and p. Each element in v is the variance of the binomial distribution specified by the corresponding elements in n and p.

The variance of the binomial distribution with parameters n and p is np(1 – p).

Extended Capabilities

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C/C++ Code Generation
Generate C and C++ code using MATLAB® Coder™.

Version History

Introduced before R2006a