Como https://gist.github.com/gallir/18f1adea5bd5c628813d pero cada persona tiene un sesgo que afecta a su elección

ties2.py

#! /usr/bin/env python

""" Execute it several times to vary the biases,
    which can be biased too
"""

import numpy.random as npr

SIZE=3030
LOOP=1000000

TIE=SIZE/2

ties=0
# Each person has a given bias
individual_bias = npr.randint(100000, size=SIZE)
print individual_bias
for i in range(1, LOOP):
    r = npr.randint(100000, size=SIZE)
    # The uniformed distributed  random is combined wth the individual bias
    a = [1 if x > individual_bias[j] else 0 for j, x in enumerate(r)]
    if sum(a) == TIE:
        ties += 1
    if i % 1000 == 0:
        print("Total: {} ties: {} prob: {}".format(i, ties, ties/float(i)))