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@stdlib/stats-binomial-test

stdlib-js68.4kApache-2.00.2.2

Exact test for the success probability in a Bernoulli experiment.

stdlib, stdmath, statistics, stats

readme (leia-me)

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Binomial Test

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Exact test for the success probability in a Bernoulli experiment.

## Installation bash npm install @stdlib/stats-binomial-test
## Usage javascript var binomialTest = require( '@stdlib/stats-binomial-test' ); #### binomialTest( x[, n][, opts] ) 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. javascript 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. javascript 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: number in the interval [0,1] giving the significance level of the hypothesis test. Default: 0.05. - alternative: Either two-sided, less or greater. 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 probability under 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. javascript 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. javascript 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. javascript 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 */
## Examples javascript var binomialTest = require( '@stdlib/stats-binomial-test' ); 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 ], // ... } */
* ## Notice This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib]. #### Community [![Chat][chat-image]][chat-url] --- ## License See [LICENSE][stdlib-license]. ## Copyright Copyright © 2016-2024. The Stdlib [Authors][stdlib-authors].
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