The simplistic answer is 1/7 but things are quite that simple. Births are not evenly distributed over days of the week.
Statistical studies of days of birth across the world have shown that the Birth Rate is lower over weekends than during weekdays - Fridays to Sundays, depending on where in the world you live. This is particularly so for induced births or ones which require surgical intervention. In such cases maternity services would wish to ensure that they were appropriately staffed: not surprisingly, medical staff wish to spend time with their families over weekends. So the probability of a Monday birth is greater than 1/7.
In the UK, between 1979 and 2014, the pattern was, Sunday (lowest), Saturday, Monday, Tuesday, Wednesday, Thursday and Friday highest). Christmas Day, Boxing Day and public holidays were excluded for this ranking,
The probability of at least 1 match is equivalent to 1 minus the probability of there being no matches. The first person's birthday can fall on any day without a match, so the probability of no matches in a group of 1 is 365/365 = 1. The second person's birthday must also fall on a free day, the probability of which is 364/365 The probability of the third person also falling on a free day is 363/365, which we must multiply by the probability of the second person's birthday being free as this must also happen. So for a group of 3 the probability of no clashes is (363*364)/(365*365). Continuing this way, the probability of no matches in a group of 41 is (365*364*363*...326*325)/36541 This can also be written 365!/(324!*36541) Which comes to 0.09685... Therefore the probability of at least one match is 1 - 0.09685 = 0.9032 So the probability of at least one match is roughly 90%
1 out of 7 I think so!
To determine the probability of 15 random people all having the same birthday, consider each person one at a time. (This is for the non leap-year case.)The probability of any person having any birthday is 365 in 365, or 1.The probability of any other person having that same birthday is 1 in 365, or 0.00274.The probability, then, of 15 random people having the same birthday is the product of these probabilities, or 0.0027414 times 1, or 1.34x10-36.Note: This answer assumes also that the distribution of birthdays for a large group of people in uniformly random over the 365 days of the year. That is probably not actually true. There are several non-random points of conception, some of which are spring, Valentine's day, and Christmas, depending of culture and religion. That makes the point of birth, nine months later, also be non-uniform, so that can skew the results.
Leaving aside leap years, the probability is 0.0137
The probability with 30 people is 0.7063 approx.
The probability of two people's birthday being the same is actually more likely than many would think. The key thing is to note that it doesn't matter what the first person's birthday is. All we need to work out is the probability that the second person has a birthday on any specific day. This probability is 1/365.25 The probability that they were born on June 10th is 1/365.25. The probability that they were born on February 2nd is 1/365.25 and the probability that they were born on the same day as you is 1/365.25
IF probability of rain is X percent then probability of no rain is 100- X percent. For example if prob of rain is 80% prob of no rain is 20%
The probability of at least 1 match is equivalent to 1 minus the probability of there being no matches. The first person's birthday can fall on any day without a match, so the probability of no matches in a group of 1 is 365/365 = 1. The second person's birthday must also fall on a free day, the probability of which is 364/365 The probability of the third person also falling on a free day is 363/365, which we must multiply by the probability of the second person's birthday being free as this must also happen. So for a group of 3 the probability of no clashes is (363*364)/(365*365). Continuing this way, the probability of no matches in a group of 41 is (365*364*363*...326*325)/36541 This can also be written 365!/(324!*36541) Which comes to 0.09685... Therefore the probability of at least one match is 1 - 0.09685 = 0.9032 So the probability of at least one match is roughly 90%
1/7.
1/7 chances
1 out of 7 I think so!
3 % No, not correct. ------------------------------------------------------------------------------------------------ The probability that a single person would have a birthday in March is 1 out of 12 (because there are 12 months in the year). Hence the probability that one of 40 students would have a birthday in March is 40 x 1/12 = 10/3 = 33.33%; More accurately March has 31 days out of 365 days min the year so the probability of one person having a birthday in March is 31/365, and for 40 students it would be 4 x 31/365 = 124/365 = 0.3397(to 4 decimal places) = 34% to nearest 1%
Rick Monday was born on November 20, 1945.
To determine the probability of 15 random people all having the same birthday, consider each person one at a time. (This is for the non leap-year case.)The probability of any person having any birthday is 365 in 365, or 1.The probability of any other person having that same birthday is 1 in 365, or 0.00274.The probability, then, of 15 random people having the same birthday is the product of these probabilities, or 0.0027414 times 1, or 1.34x10-36.Note: This answer assumes also that the distribution of birthdays for a large group of people in uniformly random over the 365 days of the year. That is probably not actually true. There are several non-random points of conception, some of which are spring, Valentine's day, and Christmas, depending of culture and religion. That makes the point of birth, nine months later, also be non-uniform, so that can skew the results.
19.4%CALCULATION:The probability of at least 2 people having the same birthday in a group of 13people is equal to one minus the probability of non of the 13 people having thesame birthday.Now, lets estimate the probability of non of the 13 people having the same birthday.(We will not consider 'leap year' for simplicity, plus it's effect on result is minimum)1. We select the 1st person. Good!.2. We select the 2nd person. The probability that he doesn't share the samebirthday with the 1st person is: 364/365.3. We select the 3rd person. The probability that he doesn't share the samebirthday with 1st and 2nd persons given that the 1st and 2nd don't share the samebirthday is: 363/365.4. And so forth until we select the 13th person. The probability that he doesn'tshare birthday with the previous 12 persons given that they also don't sharebirthdays among them is: 353/365.5. Then the probability that non of the 13 people share birthdays is:P(non of 13 share bd) = (364/365)(363/365)(362/365)∙∙∙(354/365)(353/365)P(non of 13 share bd) ≈ 0.805589724...Finally, the probability that at least 2 people share a birthday in a group of 13people is ≈ 1 - 0.80558... ≈ 0.194 ≈ 19.4%The above expression can be generalized to give the probability of at least x =2people sharing a birthday in a group of n people as:P(x≥2,n) = 1 - (1/365)n [365!/(365-n)!]
monday
Leaving aside leap years, the probability is 0.0137