docstr: Test if the p_value returned by target_real_feature_binary_test is
  low enough for highly significant features.
docstr_tok: ["Test","if","the","p_value","returned","by","target_real_feature_binary_test","is","low","enough","for","highly","significant","features","."]
code: def test_feature_selection_target_realvalued_features_binary(
      self, maximal_p_value_for_significant_features, binary_feature
  ):
      """
      Test if the p_value returned by target_real_feature_binary_test is
      low enough for highly significant features.
      """
      y = binary_feature * pd.Series(
          np.random.normal(0, 1, 250)
      ) + pd.Series(np.random.normal(0, 0.25, 250))
  
      p_value = target_real_feature_binary_test(binary_feature, y)
      assert maximal_p_value_for_significant_features > p_value
  
imports: import numpy
  import pandas
  import pytest
  from tsfresh.defaults import TEST_FOR_BINARY_TARGET_REAL_FEATURE
  from tsfresh.feature_selection.significance_tests import target_binary_feature_binary_test, target_binary_feature_real_test, target_real_feature_binary_test, target_real_feature_real_test
label_desc: Use image node_id 5 for calling the TestSignificant obj's underlying member method code with example usage: obj.test_feature_selection_target_realvalued_features_binary(maximal_p_value_for_significant_features, binary_feature) without return types