> For the complete documentation index, see [llms.txt](https://brianbuccaneer.gitbook.io/bottlenose/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://brianbuccaneer.gitbook.io/bottlenose/dev-2/data-analysis/rxstats/operators/variance.md).

# variance

## Description

Computes the variance of an `Observable` using \[Welford's Online Algorithm]\(\[<https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Welford's_online_algorithm](https://en.wikipedia.org/wiki/Algorithms_for_calculating_variance#Welford's_online_algorithm)\\>).

By default, it will compute the sample variance.

## Examples

### Sample Variance

```javascript
import { from } from 'rxjs';
import { takeLast } from 'rxjs';
import { variance } from '@bottlenose/rxstats';

const variance$ = from([600, 470, 170, 430, 300]).pipe(
  variance(),
  takeLast(1)
);

variance$.subscribe(console.log);
// Output:
// 27130
```

### Population Variance

```javascript
import { from } from 'rxjs';
import { takeLast } from 'rxjs';
import { variance } from '@bottlenose/rxstats';

const variance$ = from([600, 470, 170, 430, 300]).pipe(
  variance(false),
  takeLast(1)
);

variance$.subscribe(console.log);
// Output:
// 21704
```

## API

```
variance(
  [initialState={index: 0, mean: 0, m2: null}],
  [sample=true]
)
```

### Since

0.1

### Parameters

None

### Options

* `initialState: Object`: Sets a [warm start](https://app.gitbook.com/@brianbuccaneer/s/rxjs-stats/guides/warmstarts) value so that the calculation can continue from a non-zero starting point (instead of a blank state). The initialState should have these keys:
  * `index: Number`: The starting index. (The total number of items in the sample minus one.)
  * `mean: Number`: The initial mean of the sample.
  * `m2: Number` The initial m2 value for the sample.  (See the [source code](https://github.com/buccaneerai/rxjs-stats/blob/operators/variance.js) to see how m2 is calculated.)
* `sample: Boolean`: The default is `true`. If `true`, then it will calculate the sample variance. Otherwise, it will calculate population variance.

### Returns

`Number`. (The current variance of the `Observable`.)