code: def test_kmf_minimum_observation_bias():
      N = 250
      kmf = KaplanMeierFitter()
      T, C = exponential_survival_data(N, 0.1, scale=10)
      B = 0.01 * T
      kmf.fit(T, C, entry=B)
      kmf.plot()
      plt.title("Should have larger variances in the tails")
  
file_path: lifelines/lifelines/tests/test_generate_datasets.py
imports: import os
  import pytest
  import matplotlib.pyplot
  from lifelines import NelsonAalenFitter, KaplanMeierFitter
  from lifelines.generate_datasets import exponential_survival_data
label_desc: Use image node_id 3 for calling a global function with example usage: test_kmf_minimum_observation_bias() without return types