6 ms·

There's a difference between random and uniformly distributed.

• wodenokoto 9y ago
  No. Numbers have to be uniformly distributed in order to be random, since Randomness is the lack of pattern or predictability in events[1]. You can randomly sample from any distribution, but as long as you do it from a non-uniform distribution, you can start predicting the pattern (e.g. if you are sampling from a gaussian, you can start predicting median value) [1] https://en.wikipedia.org/wiki/Randomness https://en.wikipedia.org/wiki/Randomness
  • Applejinx 9y ago
    um no. Even on an infinite sequence, it's infinitely unlikely to get a flat distribution. That's what's annoying about real randomness, compared to 'a flat distribution'.
    • matthewbauer 9y ago
      Well don’t they flatten out over time? That’s my understanding of randomness any way...
      • TheCoelacanth 9y ago
        Do you think that the sum of rolling two dice isn't random? That isn't a uniform distribution.
        • matthewbauer 9y ago
          I guess that’s true.
          • candiodari 9y ago
            More generally, one should probably say that random numbers taken from a distribution match that distribution. Taken to an extreme one might ask, can you predict random numbers taken from a collection with only one element. Obviously you can predict the next number. It'd be like a roulette wheel with only red numbers. The outcome is random, but perfectly predictable to be red.
      • Sammi 9y ago
        Yes it will. This is called the Law of Large Numbers: https://en.wikipedia.org/wiki/Law_of_large_numbers https://en.wikipedia.org/wiki/Law_of_large_numbers
  • TheCoelacanth 9y ago
    If you follow that assertion, a great number of mathematical concepts become meaningless, e.g. probability distribution. That assertion is even at odds with the second and third sentences of the article you linked. > A random sequence of events, symbols or steps has no order and does not follow an intelligible pattern or combination. Individual random events are by definition unpredictable, but in many cases the frequency of different outcomes over a large number of events (or "trials") is predictable. For example, when throwing two dice, the outcome of any particular roll is unpredictable, but a sum of 7 will occur twice as often as 4. In this view, randomness is a measure of uncertainty of an outcome, rather than haphazardness, and applies to concepts of chance, probability, and information entropy.
    • candiodari 9y ago
      It's funny how this thread shows the exact problem identified in the article : a LOT of people have some basic idea of how to answer the question, and come up with strong opinions they "know" are right, and arguing with others. Fact of the matter is that the question is too general, and there are no real answers to it that aren't extremely general themselves. (One mistake in your response would be that obviously random numbers are taken from a particular distribution, and of course there is some information there about what to expect the next random number to be. Taken to an extreme you can take random numbers from the collection {1}. Can you predict what the next random number will be ? I think I can ... Too general questions means you have to take trivial cases into account) I wonder how many of the posters into this thread would reject candidates based on the candidates strongly disagreeing with their statements. Especially because I've got a degree in statistics and I would agree with that this question can't be answered.