
{{alias}}( NX, NY, alt, alpha, d, sdx, x, sx, sdy, y, sy, out )
    Computes a two-sample Z-test.

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

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

    Parameters
    ----------
    NX: integer
        Number of indexed elements in `x`.

    NY: integer
        Number of indexed elements in `y`.

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

        - two-sided: `x` has the same mean as `y`.
        - greater: `x` has a larger mean than `y`.
        - less: `x` has a smaller mean than `y`.

    alpha: number
        Significance level.

    d: number
        Difference in means under the null hypothesis.

    sdx: number
        Known standard deviation of `x`.

    x: Array|TypedArray|Object
        First input array.

    strideX: integer
        Stride length for `x`.

    sdy: number
        Known standard deviation of `y`.

    y: Array|TypedArray|Object
        Second input array.

    strideY: integer
        Stride length for `y`.

    out: Object
        Output results object.

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

    Examples
    --------
    > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
    > var x = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
    > var NX = x.length;
    > var NY = y.length;
    > var alt = 'two-sided';
    > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}();
    > var res = {{alias}}( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 2.0, y, 1, out );
    > res.toString()


{{alias}}.ndarray( NX, NY, alt, alpha, d, sdx, x, sx, ox, sdy, y, sy, oy, out )
    Computes a two-sample Z-test using alternative indexing semantics.

    While typed array views mandate a view offset based on the underlying
    buffer, offset parameters support indexing semantics based on starting
    indices.

    Parameters
    ----------
    NX: integer
        Number of indexed elements in `x`.

    NY: integer
        Number of indexed elements in `y`.

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

        - two-sided: `x` has the same mean as `y`.
        - greater: `x` has a larger mean than `y`.
        - less: `x` has a smaller mean than `y`.

    alpha: number
        Significance level.

    d: number
        Difference in means under the null hypothesis.

    sdx: number
        Known standard deviation of `x`.

    x: Array|TypedArray|Object
        First input array.

    strideX: integer
        Stride length for `x`.

    offsetX: integer
        Starting index for `x`.

    sdy: number
        Known standard deviation of `y`.

    y: Array|TypedArray|Object
        Second input array.

    strideY: integer
        Stride length for `y`.

    offsetY: integer
        Starting index for `y`.

    out: Object
        Output results object.

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

    Examples
    --------
    > var x = [ 4.0, 4.0, 6.0, 6.0, 5.0 ];
    > var y = [ 3.0, 3.0, 5.0, 7.0, 7.0 ];
    > var NX = x.length;
    > var NY = y.length;
    > var alt = 'two-sided';
    > var out = new {{alias:@stdlib/stats/base/ztest/two-sample/results/float64}}();
    > var res = {{alias}}.ndarray( NX, NY, alt, 0.05, 0.0, 1.0, x, 1, 0, 2.0, y, 1, 0, out );
    > res.toString()

    See Also
    --------

