BUG: Issue pandas-dev#29128 Series.var not returning the correct result (pandas-dev#29353)

Author: HubertKl

doc/source/whatsnew/v1.0.0.rst

@@ -342,6 +342,7 @@ Numeric
 - :class:`DataFrame` flex inequality comparisons methods (:meth:`DataFrame.lt`, :meth:`DataFrame.le`, :meth:`DataFrame.gt`, :meth: `DataFrame.ge`) with object-dtype and ``complex`` entries failing to raise ``TypeError`` like their :class:`Series` counterparts (:issue:`28079`)
 - Bug in :class:`DataFrame` logical operations (`&`, `|`, `^`) not matching :class:`Series` behavior by filling NA values (:issue:`28741`)
 - Bug in :meth:`DataFrame.interpolate` where specifying axis by name references variable before it is assigned (:issue:`29142`)
+- Bug in :meth:`Series.var` not computing the right value with a nullable integer dtype series not passing through ddof argument (:issue:`29128`)
 - Improved error message when using `frac` > 1 and `replace` = False (:issue:`27451`)
 - Bug in numeric indexes resulted in it being possible to instantiate an :class:`Int64Index`, :class:`UInt64Index`, or :class:`Float64Index` with an invalid dtype (e.g. datetime-like) (:issue:`29539`)
 - Bug in :class:`UInt64Index` precision loss while constructing from a list with values in the ``np.uint64`` range (:issue:`29526`)

pandas/core/arrays/integer.py

@@ -647,7 +647,7 @@ def _reduce(self, name, skipna=True, **kwargs):
             data[mask] = self._na_value
 
         op = getattr(nanops, "nan" + name)
-        result = op(data, axis=0, skipna=skipna, mask=mask)
+        result = op(data, axis=0, skipna=skipna, mask=mask, **kwargs)
 
         # if we have a boolean op, don't coerce
         if name in ["any", "all"]:

pandas/tests/arrays/test_integer.py

@@ -829,6 +829,26 @@ def test_arrow_array(data):
     assert arr.equals(expected)
 
 
+@pytest.mark.parametrize(
+    "pandasmethname, kwargs",
+    [
+        ("var", {"ddof": 0}),
+        ("var", {"ddof": 1}),
+        ("kurtosis", {}),
+        ("skew", {}),
+        ("sem", {}),
+    ],
+)
+def test_stat_method(pandasmethname, kwargs):
+    s = pd.Series(data=[1, 2, 3, 4, 5, 6, np.nan, np.nan], dtype="Int64")
+    pandasmeth = getattr(s, pandasmethname)
+    result = pandasmeth(**kwargs)
+    s2 = pd.Series(data=[1, 2, 3, 4, 5, 6], dtype="Int64")
+    pandasmeth = getattr(s2, pandasmethname)
+    expected = pandasmeth(**kwargs)
+    assert expected == result
+
+
 # TODO(jreback) - these need testing / are broken
 
 # shift