code: def _tie_correct(sample):
      
      tc = 0
      n = sum(sample.values())
  
      if n < 2:
          return 1.0  # Avoid a ``ZeroDivisionError``.
  
      for k in sorted(sample.keys()):
          tc += math.pow(sample[k], 3) - sample[k]
      tc = 1 - tc / (math.pow(n, 3) - n)
  
      return tc
docs: Returns the tie correction value for U.
  
      See: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.tiecorrect.html