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stats-strided-ztest2

Compute a two-sample Z-test.

https://github.com/stdlib-js/stats-strided-ztest2

Science Score: 44.0%

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array hypothesis javascript math mathematics node node-js nodejs normality statistics stats stdlib strided strided-array testing typed z-test ztest
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Compute a two-sample Z-test.

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array hypothesis javascript math mathematics node node-js nodejs normality statistics stats stdlib strided strided-array testing typed z-test ztest
Created 7 months ago · Last pushed 7 months ago
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README.md

About stdlib...

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ztest2

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

Compute a two-sample Z-test.

A Z-test commonly refers to a two-sample location test which compares the means of two independent sets of measurements `X` and `Y` when the population standard deviations are known. A Z-test supports testing three different null hypotheses `H0`: - `H0: μX - μY ≥ Δ` versus the alternative hypothesis `H1: μX - μY < Δ`. - `H0: μX - μY ≤ Δ` versus the alternative hypothesis `H1: μX - μY > Δ`. - `H0: μX - μY = Δ` versus the alternative hypothesis `H1: μX - μY ≠ Δ`. Here, `μX` and `μY` are the true population means of samples `X` and `Y`, respectively, and `Δ` is the hypothesized difference in means (typically `0` by default).
## Installation ```bash npm install @stdlib/stats-strided-ztest2 ``` 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 ztest2 = require( '@stdlib/stats-strided-ztest2' ); ``` #### ztest2( NX, NY, alternative, alpha, diff, sigmax, x, strideX, sigmay, y, strideY, out ) Computes a two-sample Z-test. ```javascript var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' ); var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ]; var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ]; var results = new Results(); var out = ztest2( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, results ); // returns {...} var bool = ( out === results ); // returns true ``` The function has the following parameters: - **NX**: number of indexed elements in `x`. - **NY**: number of indexed elements in `y`. - **alternative**: [alternative hypothesis][@stdlib/stats/base/ztest/alternatives]. - **alpha**: significance level. - **diff**: difference in means under the null hypothesis. - **sigmax**: known standard deviation of `x`. - **x**: first input array. - **strideX**: stride length for `x`. - **sigmay**: known standard deviation of `y`. - **y**: second input array. - **strideY**: stride length for `y`. - **out**: output [results object][@stdlib/stats/base/ztest/two-sample/results/float64]. The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to perform a two-sample Z-test over every other element in `x` and `y`, ```javascript var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' ); var x = [ 4.0, 0.0, 4.0, 0.0, 6.0, 0.0, 6.0, 0.0, 5.0, 0.0 ]; var y = [ 3.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0, 7.0, 0.0 ]; var results = new Results(); var out = ztest2( 5, 5, 'two-sided', 0.05, 0.0, 1.0, x, 2, 2.0, y, 2, results ); // returns {...} var bool = ( out === results ); // returns true ``` Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views. ```javascript var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' ); var Float64Array = require( '@stdlib/array-float64' ); var x0 = new Float64Array( [ 0.0, 4.0, 4.0, 6.0, 6.0, 5.0 ] ); var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var y0 = new Float64Array( [ 0.0, 3.0, 3.0, 5.0, 7.0, 7.0 ] ); var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 ); // start at 2nd element var results = new Results(); var out = ztest2( 5, 5, 'two-sided', 0.05, 0.0, 1.0, x1, 1, 2.0, y1, 1, results ); // returns {...} var bool = ( out === results ); // returns true ``` #### ztest2.ndarray( NX, NY, alternative, alpha, diff, sigmax, x, strideX, offsetX, sigmay, y, strideY, offsetY, out ) Computes a two-sample Z-test using alternative indexing semantics. ```javascript var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' ); var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ]; var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ]; var results = new Results(); var out = ztest2.ndarray( x.length, y.length, 'two-sided', 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, results ); // returns {...} var bool = ( out === results ); // returns true ``` The function has the following additional parameters: - **offsetX**: starting index for `x`. - **offsetY**: starting index for `y`. While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, offset parameters support indexing semantics based on starting indices. For example, to perform a two-sample Z-test over every other element in `x` and `y` starting from the second element ```javascript var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' ); var x = [ 0.0, 4.0, 0.0, 4.0, 0.0, 6.0, 0.0, 6.0, 0.0, 5.0 ]; var y = [ 0.0, 3.0, 0.0, 3.0, 0.0, 5.0, 0.0, 7.0, 0.0, 7.0 ]; var results = new Results(); var out = ztest2.ndarray( 5, 5, 'two-sided', 0.05, 0.0, 1.0, x, 2, 1, 2.0, y, 2, 1, results ); // returns {...} var bool = ( out === results ); // returns true ```
## Notes - As a general rule of thumb, a Z-test is most reliable when `N >= 50`. For smaller sample sizes or when the standard deviations are unknown, prefer a t-test. - Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array-base/accessor`][@stdlib/array/base/accessor]). - Depending on the environment, the typed versions ([`dztest2`][@stdlib/stats/strided/dztest2], [`sztest2`][@stdlib/stats/strided/sztest2], etc.) are likely to be significantly more performant.
## Examples ```javascript var Results = require( '@stdlib/stats-base-ztest-two-sample-results-float64' ); var normal = require( '@stdlib/random-array-normal' ); var ztest2 = require( '@stdlib/stats-strided-ztest2' ); var x = normal( 1000, 4.0, 2.0, { 'dtype': 'generic' }); var y = normal( 800, 3.0, 2.0, { 'dtype': 'generic' }); var results = new Results(); var out = ztest2( x.length, y.length, 'two-sided', 0.05, 1.0, 2.0, x, 1, 2.0, y, 1, results ); // 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].

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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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