
{{alias}}( N, alternative, alpha, mu, sigma, x, strideX, out )
    Computes a one-sample Z-test for a single-precision floating-point strided
    array.

    The `N` and stride parameters determine which elements in the strided array
    are accessed at runtime.

    Indexing is relative to the first index. To introduce an offset, use a typed
    array view.

    Parameters
    ----------
    N: integer
        Number of indexed elements.

    alternative: string
        Alternative hypothesis. Must be one of the following:

        - two-sided: mean is not equal to null value.
        - greater: mean is larger than null value.
        - less: mean is less than null value.

    alpha: number
        Significance level.

    mu: number
        Value of the mean under the null hypothesis.

    sigma: number
        Known standard deviation.

    x: Float32Array
        Input array.

    strideX: integer
        Stride length.

    out: Object
        Output results object.

    Returns
    -------
    out: Object
        Results object.

    Examples
    --------
    > var x = new {{alias:@stdlib/array/float32}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
    > var N = x.length;
    > var alt = 'two-sided';
    > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float32}}();
    > var res = {{alias}}( N, alt, 0.05, 0.0, 1.0, x, 1, out );
    > res.toString()


{{alias}}.ndarray( N, alternative, alpha, mu, sigma, x, strideX, offsetX, out )
    Computes a one-sample Z-test for a single-precision floating-point strided
    array using alternative indexing semantics.

    While typed array views mandate a view offset based on the underlying
    buffer, the offset parameter supports indexing semantics based on a starting
    index.

    Parameters
    ----------
    N: integer
        Number of indexed elements.

    alternative: string
        Alternative hypothesis. Must be one of the following:

        - two-sided: mean is not equal to null value.
        - greater: mean is larger than null value.
        - less: mean is less than null value.

    alpha: number
        Significance level.

    mu: number
        Value of the mean under the null hypothesis.

    sigma: number
        Known standard deviation.

    x: Float32Array
        Input array.

    strideX: integer
        Stride length.

    offsetX: integer
        Starting index.

    out: Object
        Output results object.

    Returns
    -------
    out: Object
        Results object.

    Examples
    --------
    > var x = new {{alias:@stdlib/array/float32}}( [ 4.0, 4.0, 6.0, 6.0, 5.0 ] );
    > var N = x.length;
    > var alt = 'two-sided';
    > var out = new {{alias:@stdlib/stats/base/ztest/one-sample/results/float32}}();
    > var res = {{alias}}.ndarray( N, alt, 0.05, 0.0, 1.0, x, 1, 0, out );
    > res.toString()

    See Also
    --------

