Pt1420 Unit 6 Research

Approximately four babies are born every second of the day in the world, that means that means that there are roughly 345,600 people that have the exact same birthday, including the same birth year. That makes you wonder, what the chances are that a pair of people in a room have the same birthday. With the application of the birthday paradox, also known as the birthday problem, these “chances” can be approximated.

The birthday paradox helps calculate the probability that within n randomly chosen people, some pair will have the same birthday. According to the pigeonhole principle, which states that if m objects are placed into n number of containers, where m > n, at least one container will carry two objects; the probability that there will be at least one pair of people that have the same birthday, will be 100%, if there are 367 people in the room. This is due to the fact that there are 366 possible birthdays, if you include February 29th, and if you have 367 people at least two of the people will have to have the same birthday. But if you have just 70 people the probability is still 99.9%, and 50% is achieved with just 23 people.

The probability that there is at least one pair that shares a birthday, in a room filled

These are elements such as location, mixed or only one generation, and twins. Location and the generation of the people can affect the outcome, because specific locations will cater more towards specific generations. With specific generations it is important to notice that there can often be a boom of the time babies are born, for example in my data, there were a lot of birthdays in the months of March and June, then compared to January or September. If there are twins in the room than the probability automatically changes to 100%, no matter how many people are in the room. All of these elements, and more can either make the probability more likely or less likely to be