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stats-base-ztest-two-sample-results-float32

Create a two-sample Z-test single-precision floating-point results object.

https://github.com/stdlib-js/stats-base-ztest-two-sample-results-float32

Science Score: 44.0%

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constructor ctor javascript node node-js nodejs results statistics stats stdlib util utilities utility utils z-test ztest
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Create a two-sample Z-test single-precision floating-point results object.

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constructor ctor javascript node node-js nodejs results statistics stats stdlib util utilities utility utils z-test ztest
Created 8 months ago · Last pushed 7 months ago
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README.md

About stdlib...

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Float32Results

NPM version Build Status Coverage Status <!-- dependencies -->

Create a two-sample Z-test single-precision floating-point results object.

## Installation ```bash npm install @stdlib/stats-base-ztest-two-sample-results-float32 ``` 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 Float32Results = require( '@stdlib/stats-base-ztest-two-sample-results-float32' ); ``` #### Float32Results( \[arg\[, byteOffset\[, byteLength]]] ) Returns a two-sample Z-test single-precision floating-point results object. ```javascript var results = new Float32Results(); // returns {...} ``` The function supports the following parameters: - **arg**: an [`ArrayBuffer`][@stdlib/array/buffer] or a data object (_optional_). - **byteOffset**: byte offset (_optional_). - **byteLength**: maximum byte length (_optional_). A data object argument is an object having one or more of the following properties: - **rejected**: boolean indicating whether the null hypothesis was rejected. - **alternative**: the alternative hypothesis (e.g., `'two-sided'`, `'less'`, or `'greater'`). - **alpha**: significance level. - **pValue**: p-value. - **statistic**: test statistic. - **ci**: confidence interval as a [`Float32Array`][@stdlib/array/float32]. - **nullValue**: difference in means under the null hypothesis. - **xmean**: sample mean of `x`. - **ymean**: sample mean of `y`. #### Float32Results.prototype.rejected Boolean indicating whether the null hypothesis was rejected. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.rejected; // returns ``` #### Float32Results.prototype.alternative The alternative hypothesis. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.alternative; // returns ``` #### Float32Results.prototype.alpha Significance level. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.alpha; // returns ``` #### Float32Results.prototype.pValue The test p-value. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.pValue; // returns ``` #### Float32Results.prototype.statistic The test statistic. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.statistic; // returns ``` #### Float32Results.prototype.ci Confidence interval. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.ci; // returns ``` #### Float32Results.prototype.nullValue Difference in means under the null hypothesis. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.nullValue; // returns ``` #### Float32Results.prototype.xmean Sample mean of `x`. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.xmean; // returns ``` #### Float32Results.prototype.ymean Sample mean of `y`. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.ymean; // returns ``` #### Float32Results.prototype.toString( \[options] ) Serializes a results object to a formatted string. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.toString(); // returns ``` The method supports the following options: - **digits**: number of digits to display after decimal points. Default: `4`. - **decision**: boolean indicating whether to show the test decision. Default: `true`. Example output: ```text Two-sample Z-test Alternative hypothesis: True difference in means is less than 1.0 pValue: 0.0406 statistic: 9.9901 95% confidence interval: [9.7821, 10.4451] Test Decision: Reject null in favor of alternative at 5% significance level ``` #### Float32Results.prototype.toJSON( \[options] ) Serializes a results object as a JSON object. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.toJSON(); // returns {...} ``` `JSON.stringify()` implicitly calls this method when stringifying a results instance. #### Float32Results.prototype.toDataView() Returns a [`DataView`][@stdlib/array/dataview] of a results object. ```javascript var results = new Float32Results(); // returns {...} // ... var v = results.toDataView(); // returns ```
## Notes - A results object is a [`struct`][@stdlib/dstructs/struct] providing a fixed-width composite data structure for storing two-sample Z-test results and providing an ABI-stable data layout for JavaScript-C interoperation.
## Examples ```javascript var Float32Array = require( '@stdlib/array-float32' ); var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float32' ); var results = new Results({ 'rejected': true, 'alpha': 0.05, 'pValue': 0.0132, 'statistic': 2.4773, 'nullValue': 0.0, 'xmean': 3.7561, 'ymean': 3.0129, 'ci': new Float32Array( [ 0.1552, 1.3311 ] ), 'alternative': 'two-sided' }); var str = results.toString({ 'format': 'linear' }); console.log( str ); ```
## C APIs
### Usage ```c #include "stdlib/stats/base/ztest/two-sample/results/float32.h" ``` #### stdlib_stats_ztest_two_sample_float32_results Structure for holding single-precision floating-point test results. ```c #include #include struct stdlib_stats_ztest_two_sample_float32_results { // Boolean indicating whether the null hypothesis was rejected: bool rejected; // Alternative hypothesis: int8_t alternative; // Significance level: float alpha; // p-value: float pValue; // Test statistic: float statistic; // Confidence interval: float ci[ 2 ]; // Difference in means under the null hypothesis: float nullValue; // Sample mean of `x`: float xmean; // Sample mean of `y`: float ymean; }; ```

* * * ## 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
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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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