diff --git a/scipy/stats/tests/test_axis_nan_policy.py b/scipy/stats/tests/test_axis_nan_policy.py
index 32ab94087..0a0f88825 100644
--- a/scipy/stats/tests/test_axis_nan_policy.py
+++ b/scipy/stats/tests/test_axis_nan_policy.py
@@ -501,6 +501,18 @@ def _axis_nan_policy_test(hypotest, args, kwds, n_samples, n_outputs, paired,
 
     assert_allclose(res_nd, res_1d, rtol=1e-14)
 
+# nan should not raise a exception in np.mean()
+# but does on some mips64el systems, triggering failure in some test cases
+# see https://github.com/scipy/scipy/issues/22360
+# and https://github.com/numpy/numpy/issues/23158
+def skip_nan_unexpected_exception():
+    try:
+        # should not raise an exception
+        with np.errstate(all='raise'):
+            x = np.asarray([1, 2, np.nan])
+            np.mean(x)
+    except:
+        pytest.skip("nan raises unexpected exception in numpy")
 
 @pytest.mark.parametrize(("hypotest", "args", "kwds", "n_samples", "n_outputs",
                           "paired", "unpacker"), axis_nan_policy_cases)
@@ -516,6 +528,24 @@ def test_axis_nan_policy_axis_is_None(hypotest, args, kwds, n_samples,
         def unpacker(res):
             return res
 
+    # skip if nan emits unexpected RuntimeWarning in np.mean()
+    # seen on mips64el, https://github.com/scipy/scipy/issues/22360
+    # Only affects nan_policy "mixed-propagate" for selected hypotests
+    if data_generator=="mixed" and nan_policy=="propagate":
+        # only skip affected hypotests
+        if hypotest.__name__ in ["iqr", "ttest_ci",
+                                 "xp_mean_1samp", "xp_mean_2samp", "xp_var",
+                                 "weightedtau", "weightedtau_weighted"]:
+            skip_nan_unexpected_exception()
+    # all_nans-propagate-ttest_ci is also affected, via scalar multiply
+    if (data_generator=="all_nans" and nan_policy=="propagate"
+        and hypotest.__name__=="ttest_ci"):
+        skip_nan_unexpected_exception()
+    # mixed-omit-xp_var is also affected, via subtract
+    if (data_generator=="mixed" and nan_policy=="omit"
+        and hypotest.__name__=="xp_var"):
+        skip_nan_unexpected_exception()
+
     rng = np.random.default_rng(0)
 
     if data_generator == "empty":