About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Exact test for the success probability in a Bernoulli experiment.
import binomialTest from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-binomial-test@esm/index.mjs';When supplied nonnegative integers x (number of successes in a Bernoulli experiment) and n (total number of trials), the function computes an exact test for the success probability in a Bernoulli experiment. Alternatively, x may be a two-element array containing the number of successes and failures, respectively.
var out = binomialTest( 550, 1000 );
/* returns
{
'rejected': true,
'pValue': ~0.001,
'statistic': 0.55,
'ci': [ ~0.519, ~0.581 ],
// ...
}
*/
out = binomialTest( [ 550, 450 ] );
/* returns
{
'rejected': true,
'pValue': ~0.001,
'statistic': 0.55,
'ci': [ ~0.519, ~0.581 ],
// ...
}
*/The returned object comes with a .print() method which when invoked will print a formatted output of the results of the hypothesis test. print accepts a digits option that controls the number of decimal digits displayed for the outputs and a decision option, which when set to false will hide the test decision.
console.log( out.print() );
/* e.g., =>
Exact binomial test
Alternative hypothesis: True correlation coefficient is not equal to 0.5
pValue: 0.0017
statistic: 0.55
95% confidence interval: [0.5186,0.5811]
Test Decision: Reject null in favor of alternative at 5% significance level
*/The function accepts the following options:
- alpha:
numberin the interval[0,1]giving the significance level of the hypothesis test. Default:0.05. - alternative: Either
two-sided,lessorgreater. Indicates whether the alternative hypothesis is that the true ratio of variances is greater than one (greater), smaller than one (less), or that the variances are the same (two-sided). Default:two-sided. - p: success
probabilityunder the null hypothesis. Default:0.5.
By default, the hypothesis test is carried out at a significance level of 0.05. To choose a different significance level, set the alpha option.
var out = binomialTest( 59, 100, {
'alpha': 0.1
});
/* returns
{
'rejected': true,
'pValue': ~0.089,
'statistic': 0.59,
'ci': [ ~0.487, ~0.687 ],
// ...
}
*/By default, a two-sided test is performed. To perform either of the one-sided tests, set the alternative option to less or greater.
out = binomialTest( 550, 1000, {
'alternative': 'greater'
});
table = out.print();
/** e.g., returns
Exact binomial test
Alternative hypothesis: True correlation coefficient is greater than 0.5
pValue: 0.0009
statistic: 0.55
95% confidence interval: [0.5235,1]
Test Decision: Reject null in favor of alternative at 5% significance level
*/
out = binomialTest( 550, 1000, {
'alternative': 'less'
});
table = out.print();
/* e.g., returns
Exact binomial test
Alternative hypothesis: True correlation coefficient is less than 0.5
pValue: 0.9993
statistic: 0.55
95% confidence interval: [0,0.5762]
Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/To test whether the success probability in the population is equal to some other value than 0.5, set the p option.
var out = binomialTest( 23, 100, {
'p': 0.2
});
/* returns
{
'rejected': false,
'pValue': ~0.453,
'statistic': 0.23,
'ci': [ ~0.152, ~0.325 ],
// ...
}
*/
var table = out.print();
/* e.g., returns
Exact binomial test
Alternative hypothesis: True correlation coefficient is not equal to 0.2
pValue: 0.4534
statistic: 0.23
95% confidence interval: [0.1517,0.3249]
Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">
import binomialTest from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-binomial-test@esm/index.mjs';
var out = binomialTest( 682, 925 );
/* returns
{
'rejected': true,
'pValue': ~3.544e-49,
'statistic': 0.737,
'ci': [ ~0.708, ~0.765 ],
// ...
}
*/
out = binomialTest( [ 682, 925 - 682 ] );
/* returns
{
'rejected': true,
'pValue': ~3.544e-49,
'statistic': 0.737,
'ci': [ ~0.708, ~0.765 ],
// ...
}
*/
out = binomialTest( 682, 925, {
'p': 0.75,
'alpha': 0.05
});
/* returns
{
'rejected': false,
'pValue': ~0.382
'statistic': 0.737,
'ci': [ ~0.708, ~0.765 ],
// ...
}
*/
out = binomialTest( 21, 40, {
'p': 0.4,
'alternative': 'greater'
});
/* returns
{
'rejected': false,
'pValue': ~0.382,
'statistic': 0.737,
'ci': [ ~0.385, 1.0 ],
// ...
}
*/
</script>
</body>
</html>This package is part of stdlib, a standard library 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.
Copyright © 2016-2024. The Stdlib Authors.