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def estimate_variances(nbr_games):
    mean_error_biased = np.zeros(nbr_games)
    mean_error_unbiased = np.zeros(nbr_games)
    for i in range(nbr_games):
        dist = np.random.normal(0, 1, 6)
        xbar = np.mean(dist)
        s2 = np.sum(np.power(dist - xbar, 2)) / nbr_games # <---- Here
        mean_error_biased[i] = np.mean(s2)
        us2 = np.sum(np.power(dist - xbar, 2)) / (nbr_games - 1) # <---- And here
        mean_error_unbiased[i] = np.mean(us2)
    return np.mean(mean_error_biased), np.mean(mean_error_unbiased)