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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _tie_correct(sample):
 """ Returns the tie correction value for U. See: https://docs.scipy.org/doc/scipy/reference/generated/scipy.stats.tiecorrect.html """

    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