diff --git a/dpnp/dpnp_iface.py b/dpnp/dpnp_iface.py
index 74d4aaed6a8..215509c1fc3 100644
--- a/dpnp/dpnp_iface.py
+++ b/dpnp/dpnp_iface.py
@@ -489,15 +489,8 @@ def get_result_array(a, out=None, casting="safe"):
             raise ValueError(
                 f"Output array of shape {a.shape} is needed, got {out.shape}."
             )
-        elif not isinstance(out, dpnp_array):
-            if isinstance(out, dpt.usm_ndarray):
-                out = dpnp_array._create_from_usm_ndarray(out)
-            else:
-                raise TypeError(
-                    "Output array must be any of supported type, but got {}".format(
-                        type(out)
-                    )
-                )
+        elif isinstance(out, dpt.usm_ndarray):
+            out = dpnp_array._create_from_usm_ndarray(out)
 
         dpnp.copyto(out, a, casting=casting)
 
diff --git a/dpnp/dpnp_iface_nanfunctions.py b/dpnp/dpnp_iface_nanfunctions.py
index b6a492f4f1c..966a2c9a578 100644
--- a/dpnp/dpnp_iface_nanfunctions.py
+++ b/dpnp/dpnp_iface_nanfunctions.py
@@ -384,7 +384,10 @@ def nanvar(
         avg = dpnp.divide(avg, cnt, out=avg)
 
         # Compute squared deviation from mean.
-        arr = dpnp.subtract(arr, avg)
+        if arr.dtype == avg.dtype:
+            arr = dpnp.subtract(arr, avg, out=arr)
+        else:
+            arr = dpnp.subtract(arr, avg)
         dpnp.copyto(arr, 0.0, where=mask)
         if dpnp.issubdtype(arr.dtype, dpnp.complexfloating):
             sqr = dpnp.multiply(arr, arr.conj(), out=arr).real
diff --git a/tests/test_statistics.py b/tests/test_statistics.py
index b0cc01ee70e..3caaaf9c805 100644
--- a/tests/test_statistics.py
+++ b/tests/test_statistics.py
@@ -66,29 +66,35 @@ def test_max_min_out(func):
     ia = dpnp.array(a)
 
     np_res = getattr(numpy, func)(a, axis=0)
+    # output is dpnp array
     dpnp_res = dpnp.array(numpy.empty_like(np_res))
     getattr(dpnp, func)(ia, axis=0, out=dpnp_res)
     assert_allclose(dpnp_res, np_res)
 
+    # output is usm array
     dpnp_res = dpt.asarray(numpy.empty_like(np_res))
     getattr(dpnp, func)(ia, axis=0, out=dpnp_res)
     assert_allclose(dpnp_res, np_res)
 
+    # output is numpy array -> Error
     dpnp_res = numpy.empty_like(np_res)
     with pytest.raises(TypeError):
         getattr(dpnp, func)(ia, axis=0, out=dpnp_res)
 
+    # output has incorrect shape -> Error
     dpnp_res = dpnp.array(numpy.empty((2, 3)))
     with pytest.raises(ValueError):
         getattr(dpnp, func)(ia, axis=0, out=dpnp_res)
 
 
 @pytest.mark.parametrize("func", ["max", "min"])
-def test_max_min_NotImplemented(func):
+def test_max_min_error(func):
     ia = dpnp.arange(5)
-
+    # where is not supported
     with pytest.raises(NotImplementedError):
         getattr(dpnp, func)(ia, where=False)
+
+    # initial is not supported
     with pytest.raises(NotImplementedError):
         getattr(dpnp, func)(ia, initial=6)