Added small tolerance for rounding errors

Author: jmafoster1

tests/testing_tests/test_causal_test_adequacy.py

@@ -41,7 +41,7 @@ def test_data_adequacy_numeric(self):
         )
         causal_test_case = CausalTestCase(
             base_test_case=base_test_case,
-            expected_causal_effect=NoEffect(),
+            expected_causal_effect=NoEffect(atol=0.05),
             estimate_type="coefficient",
             estimator=estimator,
         )
@@ -53,7 +53,7 @@ def test_data_adequacy_numeric(self):
             delta=1.0,
             msg=f"Expected kurtosis near 0, got {adequacy_metric.kurtosis['test_input']}",
         )  # This adds a numerical tolerance for Pandas
-        self.assertEqual(adequacy_metric.passing, 91, f"Expected passing 91 not {adequacy_metric.passing}")
+        self.assertEqual(adequacy_metric.passing, 100, f"Expected passing 100 not {adequacy_metric.passing}")
         self.assertEqual(adequacy_metric.successful, 100, f"Expected successful 100 not {adequacy_metric.successful}")
 
     def test_data_adequacy_categorical(self):
@@ -63,7 +63,7 @@ def test_data_adequacy_categorical(self):
         estimator = LinearRegressionEstimator(base_test_case=base_test_case, adjustment_set={})
         causal_test_case = CausalTestCase(
             base_test_case=base_test_case,
-            expected_causal_effect=NoEffect(),
+            expected_causal_effect=NoEffect(ctol=0.05),
             estimate_type="coefficient",
             estimator=estimator,
         )