This week we will run an anecdotal workflow to prove the Birthday Paradox! The Birthday paradox simply refers to the phenomenon that if you assembled 23 people into one room, the chances of two people having the same birthday are 50-50. We could 'math' this out, but why not just assembles 100s of thousands of people in the seconds to prove it?
In this challenge, your goal is to build a table that increment group sizes from 2 people all the way to 50 people. In each of those group sizes, run 1000 random trials and see what percent of groups had at least one set of people match. Why 1000? Theoretically, the more trials you run, the more likely you are to get a refined percent (e.g. flipping a coin four times may not a perfect 50-50 chance where it would be much closer after 1000 flips).
Due to the nature of this challenge, you will need to generate your own data! I have provided a sample output of mine, but since we are randomly assigning birthdays, you may find small differences in our answers. At what group size did it exceed 75% chance? 90% chance?