4 ms·

> one expects to see if one "rolls the dice" 10 million times. This study is based on the catalogue of 600 million objects, 60 times more than 10 million times

by acqq 7y ago

> one expects to see if one "rolls the dice" 10 million times. This study is based on the catalogue of 600 million objects, 60 times more than 10 million times: "In this latest study they compared 600 million objects in the USNO catalogue with a collection put together by the University of Hawaii's Pan-STARR system." "In an earlier study Villarroel and her team compared the positions of some 10 million objects" Emphasis mine.

shadowgovt 7y ago
Ah, good catch. So it's even likelier than I anticipate that some errors of improbable cause were observed.
- perl4ever 7y ago
  I'm surprised that given the amount of data people often deal with at work these days, that more people don't have an intuition for how unlikely coincidences happen when you're dealing with vast numbers of things.
  - bookofjoe 7y ago
    >In probability theory, the birthday problem or birthday paradox concerns the probability that, in a set of n randomly chosen people, some pair of them will have the same birthday. By the pigeonhole principle, the probability reaches 100% when the number of people reaches 367 (since there are only 366 possible birthdays, including February 29). However, 99.9% probability is reached with just 70 people, and 50% probability with 23 people. These conclusions are based on the assumption that each day of the year (excluding February 29) is equally probable for a birthday. Actual birth records show that different numbers of people are born on different days. In this case, it can be shown that the number of people required to reach the 50% threshold is 23 or fewer.[1] For example, if half the people were born on one day and the other half on another day, then any two people would have a 50% chance of sharing a birthday. It may well seem surprising that a group of just 23 individuals is required to reach a probability of 50% that at least two individuals in the group have the same birthday: this result is perhaps made more plausible by considering that the comparisons of birthday will actually be made between every possible pair of individuals = 23 × 22/2 = 253 comparisons, which is well over half the number of days in a year (183 at most), as opposed to fixing on one individual and comparing his or her birthday to everyone else's. From:https://en.wikipedia.org/wiki/Birthday_problem https://en.wikipedia.org/wiki/Birthday_problem
    - deleted 7y ago
      [deleted]

by acqq 7y ago

shadowgovt 7y ago

Ah, good catch. So it's even likelier than I anticipate that some errors of improbable cause were observed.

perl4ever 7y ago
I'm surprised that given the amount of data people often deal with at work these days, that more people don't have an intuition for how unlikely coincidences happen when you're dealing with vast numbers of things.
- bookofjoe 7y ago
  >In probability theory, the birthday problem or birthday paradox concerns the probability that, in a set of n randomly chosen people, some pair of them will have the same birthday. By the pigeonhole principle, the probability reaches 100% when the number of people reaches 367 (since there are only 366 possible birthdays, including February 29). However, 99.9% probability is reached with just 70 people, and 50% probability with 23 people. These conclusions are based on the assumption that each day of the year (excluding February 29) is equally probable for a birthday. Actual birth records show that different numbers of people are born on different days. In this case, it can be shown that the number of people required to reach the 50% threshold is 23 or fewer.[1] For example, if half the people were born on one day and the other half on another day, then any two people would have a 50% chance of sharing a birthday. It may well seem surprising that a group of just 23 individuals is required to reach a probability of 50% that at least two individuals in the group have the same birthday: this result is perhaps made more plausible by considering that the comparisons of birthday will actually be made between every possible pair of individuals = 23 × 22/2 = 253 comparisons, which is well over half the number of days in a year (183 at most), as opposed to fixing on one individual and comparing his or her birthday to everyone else's. From:https://en.wikipedia.org/wiki/Birthday_problem https://en.wikipedia.org/wiki/Birthday_problem
  - deleted 7y ago
    [deleted]