@stdlib/stats-chi2test

Perform a chi-square independence test.

https://github.com/stdlib-js/stats-chi2test

Science Score: 44.0%

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Keywords

2d categorical contingency discrete hypothesis independence javascript math mathematics node node-js nodejs statistics stats stdlib summary table test

Last synced: 6 months ago · JSON representation ·

Repository

Perform a chi-square independence test.

Basic Info

Host: GitHub
Owner: stdlib-js
License: apache-2.0
Language: JavaScript
Default Branch: main
Homepage: https://github.com/stdlib-js/stdlib
Size: 7.76 MB

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2d categorical contingency discrete hypothesis independence javascript math mathematics node node-js nodejs statistics stats stdlib summary table test

Created over 4 years ago · Last pushed 6 months ago

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Readme Changelog Contributing License Code of conduct Citation Security

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!

Chi-square independence test

Perform a chi-square independence test.

## Installation ```bash npm install @stdlib/stats-chi2test ``` Alternatively, - To load the package in a website via a `script` tag without installation and bundlers, use the [ES Module][es-module] available on the [`esm`][esm-url] branch (see [README][esm-readme]). - If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions). - For use in Observable, or in browser/node environments, use the [Universal Module Definition (UMD)][umd] build available on the [`umd`][umd-url] branch (see [README][umd-readme]). The [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships. To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

## Usage ```javascript var chi2test = require( '@stdlib/stats-chi2test' ); ``` #### chi2test( x\[, options] ) Computes a chi-square independence test for the **null hypothesis** that the joint distribution of the observed frequencies is the product of the row and column marginals (i.e., that the row and column variables are independent). ```javascript // 2x2 contigency table: var x = [ [ 20, 30 ], [ 30, 20 ] ]; var res = chi2test( x ); var o = res.toJSON(); /* returns { 'rejected': false, 'alpha': 0.05, 'pValue': ~0.072, 'df': 1, 'statistic': 3.24, ... } */ ``` The function accepts the following `options`: - **alpha**: significance level of the hypothesis test. Must be on the interval `[0,1]`. Default: `0.05`. - **correct**: `boolean` indicating whether to use Yates' continuity correction when provided a 2x2 contingency table. Default: `true`. By default, the test is performed at a significance level of `0.05`. To adjust the significance level, set the `alpha` option. ```javascript var x = [ [ 20, 30 ], [ 30, 20 ] ]; var opts = { 'alpha': 0.1 }; var res = chi2test( x, opts ); var o = res.toJSON(); /* returns { 'rejected': true, 'alpha': 0.1, 'pValue': ~0.072, 'df': 1, 'statistic': 3.24, ... } */ ``` By default, the function applies Yates' continuity correction for 2x2 contingency tables. To disable the continuity correction, set `correct` to `false`. ```javascript var x = [ [ 20, 30 ], [ 30, 20 ] ]; var opts = { 'correct': false }; var res = chi2test( x, opts ); var o = res.toJSON(); /* returns { 'rejected': true, 'alpha': 0.05, 'pValue': ~0.046, 'df': 1, 'statistic': 4, ... } */ ``` The function returns a results `object` having the following properties: - **alpha**: significance level. - **rejected**: `boolean` indicating the test decision. - **pValue**: test p-value. - **statistic**: test statistic. - **df**: degrees of freedom. - **expected**: expected observation frequencies. - **method**: test name. - **toString**: serializes results as formatted test output. - **toJSON**: serializes results as a JSON object. To print formatted test output, invoke the `toString` method. The method accepts the following options: - **digits**: number of displayed decimal digits. Default: `4`. - **decision**: `boolean` indicating whether to show the test decision. Default: `true`. ```javascript var x = [ [ 20, 30 ], [ 30, 20 ] ]; var res = chi2test( x ); var table = res.toString({ 'decision': false }); /* e.g., returns Chi-square independence test Null hypothesis: the two variables are independent pValue: 0.0719 statistic: 3.24 degrees of freedom: 1 */ ```

## Notes - The chi-square approximation may be incorrect if the observed or expected frequencies in each category are too small. Common practice is to require frequencies **greater than** five. The Yates' continuity correction is enabled by default for 2x2 tables to account for this, although it tends to over-correct.

## Examples ```javascript var array = require( '@stdlib/ndarray-array' ); var chi2test = require( '@stdlib/stats-chi2test' ); /* * Data from students in grades 4-6 on whether good grades, athletic ability, or popularity are most important to them: * * Source: Chase, M.A and Dummer, G.M. (1992), "The Role of Sports as a Social Determinant for Children" */ var table = array([ /* Grades Popularity Sports */ [ 63, 31, 25 ], // 4th [ 88, 55, 33 ], // 5th [ 96, 55, 32 ] // 6th ]); // Assess whether the grade level and the students' goals are independent of each other: var out = chi2test( table ); // returns {...} console.log( out.toString() ); ```

* * * ## 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 © 2016-2025. The Stdlib [Authors][stdlib-authors].

Owner

Name: stdlib
Login: stdlib-js
Kind: organization

Website: https://stdlib.io
Twitter: stdlibjs
Repositories: 3,692
Profile: https://github.com/stdlib-js

Standard library for JavaScript.

Citation (CITATION.cff)

cff-version: 1.2.0
title: stdlib
message: >-
  If you use this software, please cite it using the
  metadata from this file.

type: software

authors:
  - name: The Stdlib Authors
    url: https://github.com/stdlib-js/stdlib/graphs/contributors

repository-code: https://github.com/stdlib-js/stdlib
url: https://stdlib.io

abstract: |
  Standard library for JavaScript and Node.js.

keywords:
  - JavaScript
  - Node.js
  - TypeScript
  - standard library
  - scientific computing
  - numerical computing
  - statistical computing

license: Apache-2.0 AND BSL-1.0

date-released: 2016

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npmjs.org: @stdlib/stats-chi2test

Perform a chi-square independence test.

Homepage: https://stdlib.io
License: Apache-2.0
Latest release: 0.2.1
published almost 2 years ago

Versions: 12
Dependent Packages: 2
Dependent Repositories: 2
Downloads: 5,570 Last month

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Forks count: 15.5%

Maintainers (4)

planeshifter rreusser stdlib-bot kgryte

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@stdlib/stats-chi2test

Science Score: 44.0%

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Chi-square independence test

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