diff --git a/tests/test_meta/test_regression_outlier.py b/tests/test_meta/test_regression_outlier.py
index 61b12b7e..2cd1fa81 100644
--- a/tests/test_meta/test_regression_outlier.py
+++ b/tests/test_meta/test_regression_outlier.py
@@ -27,7 +27,7 @@ def test_obvious_example():
     X = np.random.normal(0, 1, (100, 1))
     y = 1 + np.sum(X, axis=1).reshape(-1, 1) + np.random.normal(0, 0.2, (100, 1))
     for i in [20, 25, 50, 80]:
-        y[i] += 2
+        y[i] += 10
     X = np.concatenate([X, y], axis=1)
 
     # fit and plot
@@ -44,7 +44,7 @@ def test_obvious_example_dataframe(frame_func):
     x = np.random.normal(0, 1, 100)
     y = 1 + x + np.random.normal(0, 0.2, 100)
     for i in [20, 25, 50, 80]:
-        y[i] += 2
+        y[i] += 10
     X = frame_func({"x": x, "y": y})
 
     # fit and plot
diff --git a/tests/test_pandas_utils/test_pandas_utils.py b/tests/test_pandas_utils/test_pandas_utils.py
index b8f956b9..fd501574 100644
--- a/tests/test_pandas_utils/test_pandas_utils.py
+++ b/tests/test_pandas_utils/test_pandas_utils.py
@@ -27,7 +27,7 @@ def test_X():
     return np.array([[-4, 2], [-2, 0], [4, -6]])
 
 
-@pytest.mark.parametrize("frame_func", [pd.DataFrame, pl.DataFrame])
+@pytest.mark.parametrize("frame_func", [pd.DataFrame, lambda data: pl.DataFrame(data, strict=False)])
 def test_add_lags_wrong_inputs(data, frame_func):
     invalid_df = [[1, 2, 3], [4, 5, 6]]
     invalid_lags = ["1", "2"]
@@ -38,7 +38,10 @@ def test_add_lags_wrong_inputs(data, frame_func):
         add_lags(invalid_df, ["X1"], 1)
 
 
-@pytest.mark.parametrize("frame_func", [pd.DataFrame, pl.DataFrame, pl.LazyFrame])
+@pytest.mark.parametrize(
+    "frame_func",
+    [pd.DataFrame, lambda data: pl.DataFrame(data, strict=False), lambda data: pl.LazyFrame(data, strict=False)],
+)
 def test_add_lags_correct_df(data, frame_func):
     test_df = frame_func(data)
     expected = frame_func({"X1": [1, 2], "X2": ["178", "154"], "X1-1": [0, 1]})
@@ -56,7 +59,7 @@ def test_add_lags_correct_X(test_X):
     assert (add_lags(test_X, [0, 1], [1, 2]) == expected).all()
 
 
-@pytest.mark.parametrize("frame_func", [pd.DataFrame, pl.DataFrame])
+@pytest.mark.parametrize("frame_func", [pd.DataFrame, lambda data: pl.DataFrame(data, strict=False)])
 def test_add_lagged_dataframe_columns(data, frame_func):
     test_df = nw.from_native(frame_func(data))
     with pytest.raises(KeyError, match="The column does not exist"):