code: def test_given_multivariate_dependent_data_when_estimate_ftest_pvalue_then_returns_pvalue_smaller_05():
      X1_training = np.random.normal(0, 1, 1000)
      X2_training = np.random.normal(0, 1, 1000)
      Y_training = (
          X1_training + X2_training + np.random.normal(0, 0.05, 1000)
      )
  
      X1_test = np.random.normal(0, 1, 1000)
      X2_test = np.random.normal(0, 1, 1000)
      Y_test = X1_test + X2_test + np.random.normal(0, 0.05, 1000)
  
      assert (
          estimate_ftest_pvalue(
              np.column_stack([X1_training, X2_training]),
              X1_training,
              Y_training,
              np.column_stack([X1_test, X2_test]),
              X1_test,
              Y_test,
          )
          < 0.05
      )
  
imports: import numpy
  import pytest
  from flaky import flaky
  from numpy.matlib import repmat
  from pytest import approx
  from dowhy.gcm.ml import create_hist_gradient_boost_classifier, create_hist_gradient_boost_regressor, create_linear_regressor, create_logistic_regression_classifier
  from dowhy.gcm.stats import estimate_ftest_pvalue, marginal_expectation, quantile_based_fwer
  from dowhy.gcm.util.general import geometric_median
label_desc: Use image node_id 15 for calling a global function with example usage: test_given_multivariate_dependent_data_when_estimate_ftest_pvalue_then_returns_pvalue_smaller_05() without return types