def METHOD_NAME(simple_dataset):
    """Test basic statistics against the Python statistics package"""
    data = json.loads(
        gs.read_command(
            "v.db.univar",
            map=simple_dataset.vector_name,
            column=simple_dataset.column_name,
            format="json",
        )
    )
    assert "statistics" in data
    stats = data["statistics"]
    assert stats["n"] == len(simple_dataset.values)
    ref_min = min(simple_dataset.values)
    ref_max = max(simple_dataset.values)
    # Using approx for all computed values, but it is really needed only for
    # stddev and variance.
    assert stats["min"] == approx(ref_min)
    assert stats["max"] == approx(ref_max)
    assert stats["range"] == approx(ref_max - ref_min)
    assert stats["sum"] == approx(sum(simple_dataset.values))
    assert stats["mean"] == approx(statistics.mean(simple_dataset.values))
    assert stats["mean_abs"] == approx(
        statistics.mean(abs(i) for i in simple_dataset.values)
    )
    assert stats["stddev"] == approx(statistics.pstdev(simple_dataset.values))
    assert stats["variance"] == approx(statistics.pvariance(simple_dataset.values))