Estimates std of underlying data, assuming each datapoint was exactly in the center of its bin.

def std(self, bessel_correction=True):
        """Estimates std of underlying data, assuming each datapoint was exactly in the center of its bin."""
        if bessel_correction:
            n = self.n
            bc = n / (n - 1)
        else:
            bc = 1
        return np.sqrt(np.average((self.bin_centers - self.mean) ** 2, weights=self.histogram)) * bc