feat(experiments): Apply new Trends continuous stats methods

posthog/hogql_queries/experiments/experiment_trends_query_runner.py

@@ -9,10 +9,10 @@
     calculate_credible_intervals,
     calculate_probabilities,
 )
-from posthog.hogql_queries.experiments.trends_statistics_v2 import (
-    are_results_significant_v2,
-    calculate_credible_intervals_v2,
-    calculate_probabilities_v2,
+from posthog.hogql_queries.experiments.trends_statistics_v2_count import (
+    are_results_significant_v2_count,
+    calculate_credible_intervals_v2_count,
+    calculate_probabilities_v2_count,
 )
 from posthog.hogql_queries.insights.trends.trends_query_runner import TrendsQueryRunner
 from posthog.hogql_queries.query_runner import QueryRunner
@@ -316,9 +316,9 @@ def run(query_runner: TrendsQueryRunner, result_key: str, is_parallel: bool):
         # Statistical analysis
         control_variant, test_variants = self._get_variants_with_base_stats(count_result, exposure_result)
         if self.stats_version == 2:
-            probabilities = calculate_probabilities_v2(control_variant, test_variants)
-            significance_code, p_value = are_results_significant_v2(control_variant, test_variants, probabilities)
-            credible_intervals = calculate_credible_intervals_v2([control_variant, *test_variants])
+            probabilities = calculate_probabilities_v2_count(control_variant, test_variants)
+            significance_code, p_value = are_results_significant_v2_count(control_variant, test_variants, probabilities)
+            credible_intervals = calculate_credible_intervals_v2_count([control_variant, *test_variants])
         else:
             probabilities = calculate_probabilities(control_variant, test_variants)
             significance_code, p_value = are_results_significant(control_variant, test_variants, probabilities)