diff --git a/python/pyspark/tests/test_statcounter.py b/python/pyspark/tests/test_statcounter.py
index 9651871e113a8..b10fe7cd911c4 100644
--- a/python/pyspark/tests/test_statcounter.py
+++ b/python/pyspark/tests/test_statcounter.py
@@ -16,6 +16,7 @@
 #
 from pyspark.statcounter import StatCounter
 from pyspark.testing.utils import ReusedPySparkTestCase
+import math
 
 
 class StatCounterTests(ReusedPySparkTestCase):
@@ -76,6 +77,31 @@ def test_merge_stats(self):
         self.assertEqual(stats.sum(), 20.0)
         self.assertAlmostEqual(stats.variance(), 1.25)
         self.assertAlmostEqual(stats.sampleVariance(), 1.4285714285714286)
+        execution_statements = [
+            StatCounter([1.0, 2.0]).mergeStats(StatCounter(range(1, 301))),
+            StatCounter(range(1, 301)).mergeStats(StatCounter([1.0, 2.0])),
+        ]
+        for stats in execution_statements:
+            self.assertEqual(stats.count(), 302)
+            self.assertEqual(stats.max(), 300.0)
+            self.assertEqual(stats.min(), 1.0)
+            self.assertAlmostEqual(stats.mean(), 149.51324503311)
+            self.assertAlmostEqual(stats.variance(), 7596.302804701549)
+            self.assertAlmostEqual(stats.sampleVariance(), 7621.539691095905)
+
+    def test_variance_when_size_zero(self):
+        # SPARK-38854: Test case to improve test coverage when
+        # StatCounter argument is empty list or None
+        arguments = [[], None]
+
+        for arg in arguments:
+            stats = StatCounter(arg)
+            self.assertTrue(math.isnan(stats.variance()))
+            self.assertTrue(math.isnan(stats.sampleVariance()))
+            self.assertEqual(stats.count(), 0)
+            self.assertTrue(math.isinf(stats.max()))
+            self.assertTrue(math.isinf(stats.min()))
+            self.assertEqual(stats.mean(), 0.0)
 
     def test_merge_stats_with_self(self):
         stats = StatCounter([1.0, 2.0, 3.0, 4.0])