def zscore(self, weighted=True, prune=False, hs_dims=None):
        """Return ndarray with cube's zscore measurements.

        Zscore is a measure of statistical significance of observed vs.
        expected counts. It's only applicable to a 2D contingency tables.
        For 3D cubes, the measures of separate slices are stacked together
        and returned as the result.

        :param weighted: Use weighted counts for zscores
        :param prune: Prune based on unweighted counts
        :param hs_dims: Include headers and subtotals (as NaN values)
        :returns zscore: ndarray representing zscore measurements
        """
        res = [s.zscore(weighted, prune, hs_dims) for s in self.slices]
        return np.array(res) if self.ndim == 3 else res[0]