diff --git a/nncf/torch/tensor_statistics/collectors.py b/nncf/torch/tensor_statistics/collectors.py
index f82877da854..e55b6ee8f10 100644
--- a/nncf/torch/tensor_statistics/collectors.py
+++ b/nncf/torch/tensor_statistics/collectors.py
@@ -254,7 +254,7 @@ class PTBatchMeanReducer(PTReducerMixIn, BatchMeanReducer):
     pass
 
 
-class PTMeanPerChReducer(PTReducerMixIn, MeanPerChReducer):
+class PTMeanPerChanelReducer(PTReducerMixIn, MeanPerChReducer):
     pass
 
 
@@ -424,7 +424,7 @@ def get_mean_stat_collector(num_samples, channel_axis, window_size=None):
     if channel_axis == 0:
         reducer = PTBatchMeanReducer()
     else:
-        reducer = PTMeanPerChReducer(channel_axis)
+        reducer = PTMeanPerChanelReducer(channel_axis)
     noop_reducer = PTNoopReducer()
 
     kwargs = {
diff --git a/tests/torch/ptq/test_reducers_and_aggregators.py b/tests/torch/ptq/test_reducers_and_aggregators.py
new file mode 100644
index 00000000000..8abf176289f
--- /dev/null
+++ b/tests/torch/ptq/test_reducers_and_aggregators.py
@@ -0,0 +1,55 @@
+# Copyright (c) 2023 Intel Corporation
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#      http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import numpy as np
+import pytest
+import torch
+
+from nncf.torch.tensor import PTNNCFTensor
+from nncf.torch.tensor_statistics.collectors import PTAbsMaxReducer
+from nncf.torch.tensor_statistics.collectors import PTAbsQuantileReducer
+from nncf.torch.tensor_statistics.collectors import PTBatchMeanReducer
+from nncf.torch.tensor_statistics.collectors import PTMaxReducer
+from nncf.torch.tensor_statistics.collectors import PTMeanPerChanelReducer
+from nncf.torch.tensor_statistics.collectors import PTMeanReducer
+from nncf.torch.tensor_statistics.collectors import PTMinReducer
+from nncf.torch.tensor_statistics.collectors import PTNNCFCollectorTensorProcessor
+from nncf.torch.tensor_statistics.collectors import PTNoopReducer
+from nncf.torch.tensor_statistics.collectors import PTQuantileReducer
+from tests.experimental.common.test_reducers_and_aggregators import TemplateTestReducersAggreagtors
+
+
+class TestReducersAggregators(TemplateTestReducersAggreagtors):
+    @pytest.fixture
+    def tensor_processor(self):
+        return PTNNCFCollectorTensorProcessor
+
+    def get_nncf_tensor(self, x: torch.Tensor):
+        return PTNNCFTensor(x)
+
+    @pytest.fixture(scope="module")
+    def reducers(self):
+        return {
+            "noop": PTNoopReducer,
+            "min": PTMinReducer,
+            "max": PTMaxReducer,
+            "abs_max": PTAbsMaxReducer,
+            "mean": PTMeanReducer,
+            "quantile": PTQuantileReducer,
+            "abs_quantile": PTAbsQuantileReducer,
+            "batch_mean": PTBatchMeanReducer,
+            "mean_per_ch": PTMeanPerChanelReducer,
+        }
+
+    def all_close(self, val, ref) -> bool:
+        val_ = torch.tensor(val)
+        ref_ = torch.tensor(ref)
+        return torch.allclose(val_, ref_) and val_.shape == ref_.shape