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The skewness for a binomial random variable is
where n
is the number of trials and p
is the success probability.
npm install @stdlib/stats-base-dists-binomial-skewness
var skewness = require( '@stdlib/stats-base-dists-binomial-skewness' );
Returns the skewness of a binomial distribution with number of trials n
and success probability p
.
var v = skewness( 20, 0.1 );
// returns ~0.596
v = skewness( 50, 0.5 );
// returns 0
If provided NaN
as any argument, the function returns NaN
.
var v = skewness( NaN, 0.5 );
// returns NaN
v = skewness( 20, NaN );
// returns NaN
If provided a number of trials n
which is not a nonnegative integer, the function returns NaN
.
var v = skewness( 1.5, 0.5 );
// returns NaN
v = skewness( -2.0, 0.5 );
// returns NaN
If provided a success probability p
outside of [0,1]
, the function returns NaN
.
var v = skewness( 20, -1.0 );
// returns NaN
v = skewness( 20, 1.5 );
// returns NaN
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var skewness = require( '@stdlib/stats-base-dists-binomial-skewness' );
var v;
var i;
var n;
var p;
for ( i = 0; i < 10; i++ ) {
n = round( randu() * 100.0 );
p = randu();
v = skewness( n, p );
console.log( 'n: %d, p: %d, skew(X;n,p): %d', n, p.toFixed( 4 ), v.toFixed( 4 ) );
}
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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