Created
October 17, 2011 15:07
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Coupon Collector's Problem applied to Birthdays
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# This is not the actual Birthday Paradox Problem. | |
# This is something similar suggested by Taylor Smith. | |
# | |
# How many people do you need in a room to have a 50% | |
# chance of having every possible birthday represented | |
# within the room? | |
# | |
# After typing all of this out, I realized that it's | |
# the same as the Coupon Collector's Problem. | |
import random | |
def main(): | |
# Total possible birthdays | |
BIRTHDAYS = 365 | |
# Number of trials to perform | |
TRIALS = 1000 | |
# Total number of people across all trials. | |
total_people = 0 | |
# Keep track of the number of completed trials | |
i = 0 | |
while i < TRIALS: | |
# This is our tally of recorded birthdays | |
calendar = [0] * BIRTHDAYS | |
# Total number of unique birthdays for this trial | |
unique_birthdays = 0 | |
# Number of people in the room | |
people_this_trial = 0 | |
while unique_birthdays < BIRTHDAYS: | |
# Allow 1 person in the room. Ask them their birthday. | |
people_this_trial += 1 | |
my_birthday = random.randint(0, BIRTHDAYS-1) | |
# Check for a unique birthday. If unique, record it. | |
if calendar[my_birthday] == 0: | |
calendar[my_birthday] += 1 | |
unique_birthdays += 1 | |
# Finished with 1 trial. Add the people_this_trial to total_people | |
total_people += people_this_trial | |
i += 1 | |
# Finally, calculate the average number of people per trial | |
# for the solution | |
average_per_trial = total_people / float(TRIALS) | |
print average_per_trial | |
if __name__ == '__main__': | |
main() |
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