time-to-botec/squiggle/node_modules/@stdlib/stats/levene-test/README.md

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# Levene's Test

> Compute Levene's test for equal variances.

<section class="intro">

Levene's test is used to test the null hypothesis that the variances of `k` groups are equal against the alternative that at least two of them are different.

</section>

<!-- /.intro -->

<section class="usage">

## Usage

```javascript
var leveneTest = require( '@stdlib/stats/levene-test' );
```

#### leveneTest( x\[, y, ..., z]\[, opts] )

Calculates Levene's test for input arrays `x`, `y`, ..., `z` holding numeric observations. 

```javascript
// Data from Hollander & Wolfe (1973), p. 116:
var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
var y = [ 3.8, 2.7, 4.0, 2.4 ];
var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];

var out = leveneTest( x, y, z );
/* returns
    {
        'rejected': false,
        'alpha': 0.05,
        'df': [ 2, 11 ],
        'pValue': ~0.1733,
        'statistic': ~2.0638,
        ...
    }
*/
```

The function accepts the following `options`:

-   **alpha**: `number` on the interval `[0,1]` giving the significance level of the hypothesis test. Default: `0.05`.
-   **groups**: an `array` of group indicators. Only applicable when providing a single numeric array holding all observations.

By default, the test is carried out at a significance level of `0.05`. To test at a different significance level, set the `alpha` option.

```javascript
var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
var y = [ 3.8, 2.7, 4.0, 2.4 ];
var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];

var out = leveneTest( x, y, z, {
    'alpha': 0.01
});
/* returns
    {
        'rejected': false,
        'alpha': 0.01,
        'df': [ 2, 11 ],
        'pValue': ~0.1733,
        'statistic': ~2.0638,
        ...
    }
*/
```

In addition to providing multiple arrays, the function supports providing a single numeric array holding all observations along with an array of group indicators.

<!-- eslint-disable array-element-newline -->

```javascript
var arr = [
    2.9, 3.0, 2.5, 2.6, 3.2,
    3.8, 2.7, 4.0, 2.4,
    2.8, 3.4, 3.7, 2.2, 2.0
];
var groups = [
    'a', 'a', 'a', 'a', 'a',
    'b', 'b', 'b', 'b',
    'c', 'c', 'c', 'c', 'c'
];
var out = leveneTest( arr, {
    'groups': groups
});
```

The returned object comes with a `.print()` method which, when invoked, prints a formatted output of test results. The method accepts the following options:

-   **digits**: number of decimal digits displayed for the outputs. Default: `4`.
-   **decision**: `boolean` indicating whether to print the test decision. Default: `true`.

```javascript
var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
var y = [ 3.8, 2.7, 4.0, 2.4 ];
var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];

var out = leveneTest( x, y, z );
console.log( out.print() );
/* =>
    Levene's test for Homogeneity of Variance

    Null hypothesis: The variances in all groups are the same.

        df 1: 2
        df 2: 11
        F score: 2.0638
        P Value: 0.1733

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/
```

</section>

<!-- /.usage -->

<section class="examples">

## Examples

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

```javascript
var leveneTest = require( '@stdlib/stats/levene-test' );

// Data from Hollander & Wolfe (1973), p. 116:
var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];
var y = [ 3.8, 2.7, 4.0, 2.4 ];
var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];

var out = leveneTest( x, y, z );
/* returns
    {
        'rejected': false,
        'alpha': 0.05,
        'df': [ 2, 11 ],
        'pValue': ~0.1733,
        'statistic': ~2.0638,
        ...
    }
*/

var table = out.print();
/* returns
    Levene's test for Homogeneity of Variance

    Null hypothesis: The variances in all groups are the same.

        df 1: 2
        df 2: 11
        F score: 2.0638
        P Value: 0.1733

    Test Decision: Fail to reject null in favor of alternative at 5% significance level
*/
```

</section>

<!-- /.examples -->

<section class="references">

</section>

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<section class="links">

</section>

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