{{alias}}( x, y[, options] )
    Computes a two-sample F-test for equal variances.

    The returned object comes with a `.print()` method which when invoked will
    print a formatted output of the results of the hypothesis test.

    Parameters
    ----------
    x: Array<number>
        First data array.

    y: Array<number>
        Second data array.

    options: Object (optional)
        Options.

    options.alpha: number (optional)
        Number in the interval `[0,1]` giving the significance level of the
        hypothesis test. Default: `0.05`.

    options.alternative: string (optional)
        Either `two-sided`, `less` or `greater`.

    options.ratio: number (optional)
        Positive number denoting the ratio of the two population variances under
        the null hypothesis. Default: `1`.

    Returns
    -------
    out: Object
        Test result object.

    out.alpha: number
        Used significance level.

    out.rejected: boolean
        Test decision.

    out.pValue: number
        p-value of the test.

    out.statistic: number
        Value of test statistic.

    out.ci: Array<number>
        1-alpha confidence interval for the ratio of variances.

    out.nullValue: number
        Assumed ratio of variances under H0.

    out.xvar: number
        Sample variance of `x`.

    out.yvar: number
        Sample variance of `y`.

    out.alternative: string
        Alternative hypothesis (`two-sided`, `less` or `greater`).

    out.dfX: number
        Numerator degrees of freedom.

    out.dfY: number
        Denominator degrees of freedom.

    out.method: string
        Name of test.

    out.print: Function
        Function to print formatted output.

    Examples
    --------
    > var x = [ 610, 610, 550, 590, 565, 570 ];
    > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];
    > var out = {{alias}}( x, y )
    {
        rejected: false,
        pValue: ~0.399,
        statistic: ~1.976,
        ci: [ ~0.374, ~13.542 ],
        // ...
    }

    // Print table output:
    > var table = out.print()
    F test for comparing two variances

    Alternative hypothesis: True ratio in variances is not equal to 1

        pValue: 0.3992
        statistic: 1.976
        variance of x: 617.5 (df of x: 5)
        variance of y: 312.5 (df of y: 7)
        95% confidence interval: [0.3739,13.5417]

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

    See Also
    --------