diff --git a/numpy/core/_methods.py b/numpy/core/_methods.py
index 51362c7614ee..953e7e1b84c2 100644
--- a/numpy/core/_methods.py
+++ b/numpy/core/_methods.py
@@ -115,10 +115,11 @@ def _var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False):
     # Note that x may not be inexact and that we need it to be an array,
     # not a scalar.
     x = asanyarray(arr - arrmean)
-    if issubclass(arr.dtype.type, nt.complexfloating):
-        x = um.multiply(x, um.conjugate(x), out=x).real
-    else:
+    if issubclass(arr.dtype.type, (nt.floating, nt.integer)):
         x = um.multiply(x, x, out=x)
+    else:
+        x = um.multiply(x, um.conjugate(x), out=x).real
+
     ret = umr_sum(x, axis, dtype, out, keepdims)
 
     # Compute degrees of freedom and make sure it is not negative.
diff --git a/numpy/core/tests/test_numeric.py b/numpy/core/tests/test_numeric.py
index 90ac43a56dc0..1822a7adf72b 100644
--- a/numpy/core/tests/test_numeric.py
+++ b/numpy/core/tests/test_numeric.py
@@ -216,6 +216,9 @@ def test_var(self):
             assert_(np.isnan(np.var([])))
             assert_(w[0].category is RuntimeWarning)
 
+        B = np.array([None, 0])
+        B[0] = 1j
+        assert_almost_equal(np.var(B), 0.25)
 
 class TestIsscalar(object):
     def test_isscalar(self):