code: def check_sample_var(sample, popvar):
      # check that population mean lies within the CI bootstrapped from the
      # sample. This used to be a chi-squared test for variance, but there were
      # too many false positives
      res = stats.bootstrap(
          (sample,),
          lambda x, axis: x.var(ddof=1, axis=axis),
          confidence_level=0.995,
      )
      conf = res.confidence_interval
      low, high = conf.low, conf.high
      assert low <= popvar <= high
  
imports: import sys
  import numpy
  import numpy.testing
  import pytest
  from pytest import raises
  from scipy.integrate import IntegrationWarning
  import itertools
  from scipy import stats
  from .common_tests import check_normalization, check_moment, check_mean_expect, check_var_expect, check_skew_expect, check_kurt_expect, check_entropy, check_private_entropy, check_entropy_vect_scale, check_edge_support, check_named_args, check_random_state_property, check_meth_dtype, check_ppf_dtype, check_cmplx_deriv, check_pickling, check_rvs_broadcast, check_freezing, check_munp_expect
  from scipy.stats._distr_params import distcont
  from scipy.stats._distn_infrastructure import rv_continuous_frozen
label_desc: Use image node_id 18 for calling a global function with example usage: check_sample_var(sample, popvar) without return types