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Apache-2.0\n\nCopyright (c) 2025 The Stdlib Authors.\n\nLicensed under the Apache License, Version 2.0 (the \"License\");\nyou may not use this file except in compliance with the License.\nYou may obtain a copy of the License at\n\n   http://www.apache.org/licenses/LICENSE-2.0\n\nUnless required by applicable law or agreed to in writing, software\ndistributed under the License is distributed on an \"AS IS\" BASIS,\nWITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\nSee the License for the specific language governing permissions and\nlimitations under the License.\n\n--\u003e\n\n\n\u003cdetails\u003e\n  \u003csummary\u003e\n    About stdlib...\n  \u003c/summary\u003e\n  \u003cp\u003eWe 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.\u003c/p\u003e\n  \u003cp\u003eThe 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.\u003c/p\u003e\n  \u003cp\u003eWhen 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.\u003c/p\u003e\n  \u003cp\u003eTo join us in bringing numerical computing to the web, get started by checking us out on \u003ca href=\"https://github.com/stdlib-js/stdlib\"\u003eGitHub\u003c/a\u003e, and please consider \u003ca href=\"https://opencollective.com/stdlib\"\u003efinancially supporting stdlib\u003c/a\u003e. We greatly appreciate your continued support!\u003c/p\u003e\n\u003c/details\u003e\n\n# dztest\n\n[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] \u003c!-- [![dependencies][dependencies-image]][dependencies-url] --\u003e\n\n\u003e Compute a one-sample Z-test for a one-dimensional double-precision floating-point ndarray.\n\n\u003csection class=\"intro\"\u003e\n\nA Z-test commonly refers to a one-sample location test which compares the mean of a set of measurements `X` to a given constant when the standard deviation is known. A Z-test supports testing three different null hypotheses `H0`:\n\n-   `H0: μ ≥ μ0` versus the alternative hypothesis `H1: μ \u003c μ0`.\n-   `H0: μ ≤ μ0` versus the alternative hypothesis `H1: μ \u003e μ0`.\n-   `H0: μ = μ0` versus the alternative hypothesis `H1: μ ≠ μ0`.\n\n\u003c/section\u003e\n\n\u003c!-- /.intro --\u003e\n\n\u003csection class=\"installation\"\u003e\n\n## Installation\n\n```bash\nnpm install @stdlib/stats-base-ndarray-dztest\n```\n\nAlternatively,\n\n-   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]).\n-   If you are using Deno, visit the [`deno`][deno-url] branch (see [README][deno-readme] for usage intructions).\n-   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]).\n\nThe [branches.md][branches-url] file summarizes the available branches and displays a diagram illustrating their relationships.\n\nTo 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.\n\n\u003c/section\u003e\n\n\u003csection class=\"usage\"\u003e\n\n## Usage\n\n```javascript\nvar dztest = require( '@stdlib/stats-base-ndarray-dztest' );\n```\n\n#### dztest( arrays )\n\nComputes a one-sample Z-test for a one-dimensional double-precision floating-point ndarray.\n\n```javascript\nvar Float64Results = require( '@stdlib/stats-base-ztest-one-sample-results-float64' );\nvar resolveEnum = require( '@stdlib/stats-base-ztest-alternative-resolve-enum' );\nvar structFactory = require( '@stdlib/array-struct-factory' );\nvar Float64Vector = require( '@stdlib/ndarray-vector-float64' );\nvar scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );\nvar ndarray = require( '@stdlib/ndarray-ctor' );\n\nvar opts = {\n    'dtype': 'float64'\n};\nvar x = new Float64Vector( [ 1.0, 3.0, 4.0, 2.0 ] );\n\nvar alt = scalar2ndarray( resolveEnum( 'two-sided' ), {\n    'dtype': 'int8'\n});\nvar alpha = scalar2ndarray( 0.05, opts );\nvar mu = scalar2ndarray( 0.0, opts );\nvar sigma = scalar2ndarray( 1.0, opts );\n\nvar ResultsArray = structFactory( Float64Results );\nvar out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );\n\nvar v = dztest( [ x, out, alt, alpha, mu, sigma ] );\n\nvar bool = ( v === out );\n// returns true\n```\n\nThe function has the following parameters:\n\n-   **arrays**: array-like object containing the following ndarrays:\n\n    -   a one-dimensional input ndarray.\n    -   a zero-dimensional output ndarray containing a [results object][@stdlib/stats/base/ztest/one-sample/results/float64].\n    -   a zero-dimensional ndarray specifying the alternative hypothesis.\n    -   a zero-dimensional ndarray specifying the significance level.\n    -   a zero-dimensional ndarray specifying the mean under the null hypothesis.\n    -   a zero-dimensional ndarray specifying the known standard deviation.\n\n\u003c/section\u003e\n\n\u003c!-- /.usage --\u003e\n\n\u003csection class=\"notes\"\u003e\n\n## Notes\n\n-   As a general rule of thumb, a Z-test is most reliable for sample sizes greater than `50`. For smaller sample sizes or when the standard deviation is unknown, prefer a t-test.\n\n\u003c/section\u003e\n\n\u003c!-- /.notes --\u003e\n\n\u003csection class=\"examples\"\u003e\n\n## Examples\n\n\u003c!-- eslint no-undef: \"error\" --\u003e\n\n```javascript\nvar Float64Results = require( '@stdlib/stats-base-ztest-one-sample-results-float64' );\nvar resolveEnum = require( '@stdlib/stats-base-ztest-alternative-resolve-enum' );\nvar structFactory = require( '@stdlib/array-struct-factory' );\nvar normal = require( '@stdlib/random-normal' );\nvar ndarray = require( '@stdlib/ndarray-ctor' );\nvar scalar2ndarray = require( '@stdlib/ndarray-from-scalar' );\nvar ndarray2array = require( '@stdlib/ndarray-to-array' );\nvar dztest = require( '@stdlib/stats-base-ndarray-dztest' );\n\nvar opts = {\n    'dtype': 'float64'\n};\n\n// Create a one-dimensional ndarray containing pseudorandom numbers drawn from a normal distribution:\nvar x = normal( [ 100 ], 0.0, 1.0, opts );\nconsole.log( ndarray2array( x ) );\n\n// Specify the alternative hypothesis:\nvar alt = scalar2ndarray( resolveEnum( 'two-sided' ), {\n    'dtype': 'int8'\n});\n\n// Specify the significance level:\nvar alpha = scalar2ndarray( 0.05, opts );\n\n// Specify the mean under the null hypothesis:\nvar mu = scalar2ndarray( 0.0, opts );\n\n// Specify the known standard deviation:\nvar sigma = scalar2ndarray( 1.0, opts );\n\n// Create a zero-dimensional results ndarray:\nvar ResultsArray = structFactory( Float64Results );\nvar out = new ndarray( Float64Results, new ResultsArray( 1 ), [], [ 0 ], 0, 'row-major' );\n\n// Perform a Z-test:\nvar v = dztest( [ x, out, alt, alpha, mu, sigma ] );\nconsole.log( v.get().toString() );\n```\n\n\u003c/section\u003e\n\n\u003c!-- /.examples --\u003e\n\n\u003c!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. --\u003e\n\n\u003csection class=\"related\"\u003e\n\n\u003c/section\u003e\n\n\u003c!-- /.related --\u003e\n\n\u003c!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --\u003e\n\n\n\u003csection class=\"main-repo\" \u003e\n\n* * *\n\n## Notice\n\nThis 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.\n\nFor 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].\n\n#### Community\n\n[![Chat][chat-image]][chat-url]\n\n---\n\n## License\n\nSee [LICENSE][stdlib-license].\n\n\n## Copyright\n\nCopyright \u0026copy; 2016-2026. The Stdlib [Authors][stdlib-authors].\n\n\u003c/section\u003e\n\n\u003c!-- /.stdlib --\u003e\n\n\u003c!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. --\u003e\n\n\u003csection class=\"links\"\u003e\n\n[npm-image]: http://img.shields.io/npm/v/@stdlib/stats-base-ndarray-dztest.svg\n[npm-url]: https://npmjs.org/package/@stdlib/stats-base-ndarray-dztest\n\n[test-image]: https://github.com/stdlib-js/stats-base-ndarray-dztest/actions/workflows/test.yml/badge.svg?branch=main\n[test-url]: https://github.com/stdlib-js/stats-base-ndarray-dztest/actions/workflows/test.yml?query=branch:main\n\n[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/stats-base-ndarray-dztest/main.svg\n[coverage-url]: https://codecov.io/github/stdlib-js/stats-base-ndarray-dztest?branch=main\n\n\u003c!--\n\n[dependencies-image]: https://img.shields.io/david/stdlib-js/stats-base-ndarray-dztest.svg\n[dependencies-url]: https://david-dm.org/stdlib-js/stats-base-ndarray-dztest/main\n\n--\u003e\n\n[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg\n[chat-url]: https://stdlib.zulipchat.com\n\n[stdlib]: https://github.com/stdlib-js/stdlib\n\n[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors\n\n[umd]: https://github.com/umdjs/umd\n[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules\n\n[deno-url]: https://github.com/stdlib-js/stats-base-ndarray-dztest/tree/deno\n[deno-readme]: https://github.com/stdlib-js/stats-base-ndarray-dztest/blob/deno/README.md\n[umd-url]: https://github.com/stdlib-js/stats-base-ndarray-dztest/tree/umd\n[umd-readme]: https://github.com/stdlib-js/stats-base-ndarray-dztest/blob/umd/README.md\n[esm-url]: https://github.com/stdlib-js/stats-base-ndarray-dztest/tree/esm\n[esm-readme]: https://github.com/stdlib-js/stats-base-ndarray-dztest/blob/esm/README.md\n[branches-url]: https://github.com/stdlib-js/stats-base-ndarray-dztest/blob/main/branches.md\n\n[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-base-ndarray-dztest/main/LICENSE\n\n[@stdlib/stats/base/ztest/one-sample/results/float64]: https://github.com/stdlib-js/stats-base-ztest-one-sample-results-float64\n\n\u003c/section\u003e\n\n\u003c!-- /.links --\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fstats-base-ndarray-dztest","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstdlib-js%2Fstats-base-ndarray-dztest","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstdlib-js%2Fstats-base-ndarray-dztest/lists"}