diff --git a/posthog/hogql_queries/experiments/test/test_trends_statistics_count.py b/posthog/hogql_queries/experiments/test/test_trends_statistics_count.py
index aad0b72c6a9fa..08748f8edd480 100644
--- a/posthog/hogql_queries/experiments/test/test_trends_statistics_count.py
+++ b/posthog/hogql_queries/experiments/test/test_trends_statistics_count.py
@@ -13,8 +13,10 @@
 from posthog.test.base import APIBaseTest
 
 
-def create_variant(key: str, count: int, exposure: int) -> ExperimentVariantTrendsBaseStats:
-    return ExperimentVariantTrendsBaseStats(key=key, count=count, exposure=exposure, absolute_exposure=exposure)
+def create_variant(key: str, count: int, exposure: float, absolute_exposure: int) -> ExperimentVariantTrendsBaseStats:
+    return ExperimentVariantTrendsBaseStats(
+        key=key, count=count, exposure=exposure, absolute_exposure=absolute_exposure
+    )
 
 
 def create_variant_with_different_exposures(
@@ -50,8 +52,15 @@ def test_small_sample_two_variants_not_significant(self):
         """Test with small sample size, two variants, no clear winner"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=10, exposure=100)
-            test = create_variant("test", count=11, exposure=100)
+            control_absolute_exposure = 100
+            control = create_variant("control", count=10, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_absolute_exposure = 100
+            test = create_variant(
+                "test",
+                count=11,
+                exposure=test_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test])
             significance, p_value = are_results_significant(control, [test], probabilities)
@@ -77,8 +86,15 @@ def test_large_sample_two_variants_significant(self):
         """Test with large sample size, two variants, clear winner"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=1000, exposure=10000)
-            test = create_variant("test", count=1200, exposure=10000)
+            control_absolute_exposure = 10000
+            control = create_variant("control", count=1000, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_absolute_exposure = 10000
+            test = create_variant(
+                "test",
+                count=1200,
+                exposure=test_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test])
             significance, p_value = are_results_significant(control, [test], probabilities)
@@ -107,8 +123,15 @@ def test_large_sample_two_variants_strongly_significant(self):
         """Test with large sample size, two variants, very clear winner"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=1000, exposure=10000)
-            test = create_variant("test", count=1500, exposure=10000)
+            control_absolute_exposure = 10000
+            control = create_variant("control", count=1000, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_absolute_exposure = 10000
+            test = create_variant(
+                "test",
+                count=1500,
+                exposure=test_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test])
             significance, p_value = are_results_significant(control, [test], probabilities)
@@ -137,10 +160,29 @@ def test_many_variants_not_significant(self):
         """Test with multiple variants, no clear winner"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=100, exposure=1000)
-            test_a = create_variant("test_a", count=98, exposure=1000)
-            test_b = create_variant("test_b", count=102, exposure=1000)
-            test_c = create_variant("test_c", count=101, exposure=1000)
+            control_absolute_exposure = 1000
+            control = create_variant("control", count=100, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_a_absolute_exposure = 1000
+            test_a = create_variant(
+                "test_a",
+                count=98,
+                exposure=test_a_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_a_absolute_exposure,
+            )
+            test_b_absolute_exposure = 1000
+            test_b = create_variant(
+                "test_b",
+                count=102,
+                exposure=test_b_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_b_absolute_exposure,
+            )
+            test_c_absolute_exposure = 1000
+            test_c = create_variant(
+                "test_c",
+                count=101,
+                exposure=test_c_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_c_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test_a, test_b, test_c])
             significance, p_value = are_results_significant(control, [test_a, test_b, test_c], probabilities)
@@ -170,10 +212,29 @@ def test_many_variants_significant(self):
         """Test with multiple variants, one clear winner"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=1000, exposure=10000)
-            test_a = create_variant("test_a", count=1050, exposure=10000)
-            test_b = create_variant("test_b", count=1500, exposure=10000)
-            test_c = create_variant("test_c", count=1100, exposure=10000)
+            control_absolute_exposure = 10000
+            control = create_variant("control", count=1000, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_a_absolute_exposure = 10000
+            test_a = create_variant(
+                "test_a",
+                count=1050,
+                exposure=test_a_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_a_absolute_exposure,
+            )
+            test_b_absolute_exposure = 10000
+            test_b = create_variant(
+                "test_b",
+                count=1500,
+                exposure=test_b_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_b_absolute_exposure,
+            )
+            test_c_absolute_exposure = 10000
+            test_c = create_variant(
+                "test_c",
+                count=1100,
+                exposure=test_c_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_c_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test_a, test_b, test_c])
             significance, p_value = are_results_significant(control, [test_a, test_b, test_c], probabilities)
@@ -211,8 +272,15 @@ def test_insufficient_sample_size(self):
         """Test with sample size below threshold"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=5, exposure=50)
-            test = create_variant("test", count=8, exposure=50)
+            control_absolute_exposure = 50
+            control = create_variant("control", count=5, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_absolute_exposure = 50
+            test = create_variant(
+                "test",
+                count=8,
+                exposure=test_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test])
             significance, p_value = are_results_significant(control, [test], probabilities)
@@ -241,8 +309,15 @@ def test_edge_cases(self):
         """Test edge cases like zero counts"""
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
-            control = create_variant("control", count=0, exposure=1000)
-            test = create_variant("test", count=0, exposure=1000)
+            control_absolute_exposure = 1000
+            control = create_variant("control", count=0, exposure=1, absolute_exposure=control_absolute_exposure)
+            test_absolute_exposure = 1000
+            test = create_variant(
+                "test",
+                count=0,
+                exposure=test_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test])
             significance, p_value = are_results_significant(control, [test], probabilities)
@@ -268,11 +343,16 @@ def test_different_relative_and_absolute_exposure(self):
 
         def run_test(stats_version, calculate_probabilities, are_results_significant, calculate_credible_intervals):
             # Control has exposure=1 (relative) but absolute_exposure=10000
-            control = create_variant_with_different_exposures(
-                "control", count=1000, exposure=1, absolute_exposure=10000
-            )
+            control_absolute_exposure = 10000
+            control = create_variant("control", count=1000, exposure=1, absolute_exposure=control_absolute_exposure)
             # Test has exposure=1.2 (relative) but absolute_exposure=12000
-            test = create_variant_with_different_exposures("test", count=1200, exposure=1.2, absolute_exposure=12000)
+            test_absolute_exposure = 12000
+            test = create_variant(
+                "test",
+                count=1200,
+                exposure=test_absolute_exposure / control_absolute_exposure,
+                absolute_exposure=test_absolute_exposure,
+            )
 
             probabilities = calculate_probabilities(control, [test])
             significance, p_value = are_results_significant(control, [test], probabilities)