npm package: @stdlib/stats-iter-variance
Description: Compute the unbiased sample variance over all iterated values.
Author: The Stdlib Authors
Latest version: 0.2.3

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  <summary>
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# itervariance

[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url] <!-- [![dependencies][dependencies-image]][dependencies-url] -->

> Compute the [unbiased sample variance][sample-variance] over all [iterated][mdn-iterator-protocol] values.

<section class="intro">

The [unbiased sample variance][sample-variance] is defined as

<!-- <equation class="equation" label="eq:unbiased_sample_variance" align="center" raw="s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2" alt="Equation for the unbiased sample variance."> -->

<div class="equation" align="center" data-raw-text="s^2 = \frac{1}{n-1} \sum_{i=0}^{n-1} ( x_i - \bar{x} )^2" data-equation="eq:unbiased_sample_variance">
    <img src="https://cdn.jsdelivr.net/gh/stdlib-js/stdlib@e7ac225deb396ee6d2b4d5fc1a2faa645582349f/lib/node_modules/@stdlib/stats/iter/variance/docs/img/equation_unbiased_sample_variance.svg" alt="Equation for the unbiased sample variance.">
    <br>
</div>

<!-- </equation> -->

</section>

<!-- /.intro -->

<!-- Package usage documentation. -->

<section class="installation">

## Installation

```bash
npm install @stdlib/stats-iter-variance
```

</section>

<section class="usage">

## Usage

```javascript
var itervariance = require( '@stdlib/stats-iter-variance' );
```

#### itervariance( iterator\[, mean] )

Computes the [unbiased sample variance][sample-variance] over all [iterated][mdn-iterator-protocol] values.

```javascript
var array2iterator = require( '@stdlib/array-to-iterator' );

var arr = array2iterator( [ 2.0, 1.0, 3.0 ] );

var s2 = itervariance( arr );
// returns 1.0
```

If the mean is already known, provide a `mean` argument.

```javascript
var array2iterator = require( '@stdlib/array-to-iterator' );

var arr = array2iterator( [ 2.0, 1.0, 3.0 ] );

var s2 = itervariance( arr, 2.0 );
// returns ~0.67
```

</section>

<!-- /.usage -->

<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="notes">

## Notes

-   If an iterated value is non-numeric (including `NaN`), the returned [`iterator`][mdn-iterator-protocol] returns `NaN`. If non-numeric iterated values are possible, you are advised to provide an [`iterator`][mdn-iterator-protocol] which type checks and handles non-numeric values accordingly.

</section>

<!-- /.notes -->

<!-- Package usage examples. -->

<section class="examples">

## Examples

<!-- eslint no-undef: "error" -->

```javascript
var runif = require( '@stdlib/random-iter-uniform' );
var itervariance = require( '@stdlib/stats-iter-variance' );

// Create an iterator for generating uniformly distributed pseudorandom numbers:
var rand = runif( -10.0, 10.0, {
    'seed': 1234,
    'iter': 100
});

// Compute the unbiased sample variance:
var s2 = itervariance( rand );
// returns <number>

console.log( 'Variance: %d.', s2 );
```

</section>

<!-- /.examples -->

<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->

<section class="references">

</section>

<!-- /.references -->

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<section class="related">

* * *

## See Also

-   <span class="package-name">[`@stdlib/stats-iter/mean`][@stdlib/stats/iter/mean]</span><span class="delimiter">: </span><span class="description">compute the arithmetic mean over all iterated values.</span>
-   <span class="package-name">[`@stdlib/stats-iter/stdev`][@stdlib/stats/iter/stdev]</span><span class="delimiter">: </span><span class="description">compute the corrected sample standard deviation over all iterated values.</span>

</section>

<!-- /.related -->

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<section class="main-repo" >

* * *

## 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 &copy; 2016-2026. The Stdlib [Authors][stdlib-authors].

</section>

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[npm-url]: https://npmjs.org/package/@stdlib/stats-iter-variance

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[stdlib]: https://github.com/stdlib-js/stdlib

[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors

[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules

[deno-url]: https://github.com/stdlib-js/stats-iter-variance/tree/deno
[deno-readme]: https://github.com/stdlib-js/stats-iter-variance/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/stats-iter-variance/tree/umd
[umd-readme]: https://github.com/stdlib-js/stats-iter-variance/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/stats-iter-variance/tree/esm
[esm-readme]: https://github.com/stdlib-js/stats-iter-variance/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/stats-iter-variance/blob/main/branches.md

[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/stats-iter-variance/main/LICENSE

[sample-variance]: https://en.wikipedia.org/wiki/Variance

[mdn-iterator-protocol]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Iteration_protocols#The_iterator_protocol

<!-- <related-links> -->

[@stdlib/stats/iter/mean]: https://www.npmjs.com/package/@stdlib/stats-iter-mean

[@stdlib/stats/iter/stdev]: https://www.npmjs.com/package/@stdlib/stats-iter-stdev

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</section>

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