code: def setup_class(cls):
      y0 = [
          112.488,
          103.738,
          86.344,
          101.708,
          95.108,
          105.931,
          95.815,
          91.864,
          102.479,
          102.644,
      ]
      y1 = [
          100.421,
          101.966,
          99.636,
          105.983,
          88.377,
          102.618,
          105.486,
          98.662,
          94.137,
          98.626,
          89.367,
          106.204,
      ]
      y2 = [
          84.846,
          100.488,
          119.763,
          103.736,
          93.141,
          108.254,
          99.510,
          89.005,
          108.200,
          82.209,
          100.104,
          103.706,
          107.067,
      ]
      y3 = [
          100.825,
          100.255,
          103.363,
          93.230,
          95.325,
          100.288,
          94.750,
          107.129,
          98.246,
          96.365,
          99.740,
          106.049,
          92.691,
          93.111,
          98.243,
      ]
  
      n_groups = 4
      arrs_w = [np.asarray(yi) for yi in [y0, y1, y2, y3]]
      nobs = np.asarray([len(yi) for yi in arrs_w])
      nobs_mean = np.mean(nobs)
      means = np.asarray([yi.mean() for yi in arrs_w])
      stds = np.asarray([yi.std(ddof=1) for yi in arrs_w])
      cls.data = arrs_w  # TODO use `data`
      cls.means = means
      cls.nobs = nobs
      cls.stds = stds
      cls.n_groups = n_groups
      cls.nobs_mean = nobs_mean
  
imports: import numpy
  from numpy.testing import assert_allclose, assert_equal
  import pytest
  from statsmodels.regression.linear_model import OLS
  import statsmodels.stats.power
  import statsmodels.stats.oneway
  from statsmodels.stats.oneway import confint_effectsize_oneway, confint_noncentrality, effectsize_oneway, anova_oneway, anova_generic, equivalence_oneway, equivalence_oneway_generic, power_equivalence_oneway, _power_equivalence_oneway_emp, f2_to_wellek, fstat_to_wellek, wellek_to_f2
  from statsmodels.stats.robust_compare import scale_transform
  from statsmodels.stats.contrast import wald_test_noncent_generic, wald_test_noncent, _offset_constraint
label_desc: Use image node_id 1 for calling the TestOnewayEquivalenc obj's underlying member method code with example usage: obj.setup_class(cls) without return types