![]() Type "diode voltage drop" into your search engine and you'll learn more than you want to know about this. You can buy boards that plug into your computer and provide quantum random values. So you subtract 0.7 and you have a random number with about 0.1 range of variation. That voltage is always about 0.7 volts, but the exact value depends on quantum effects in the silicon. One classic example is to measure very precisely the voltage across a diode. The only way to get truly random numbers is to build a device that takes advantage of quantum randomness. And Google's didn't pick all different numbers on purpose either.īut neither ours nor theirs is really a random number generator they generate pseudorandom numbers, which means that each value is generated from the past history algorithmically, but using algorithms that have been shown to have a good distribution. I promise that our random number generator didn't pick prime numbers for you on purpose. I believe, although I've never studied statistics and it's been a long time since probability in high school, that you actually want to pick a lot of numbers a lot of times, so it's better to make ten trials of 1000 numbers each than one big trial of 10,000 numbers, because no matter how big the trial you might happen to get weird results, but you're much less likely to get the same sort of weird results ten times just by chance. So, yeah, you have to pick a lot of numbers and then you can see how they're distributed. Once you know the number, it's constant! When people say "a random number" they mean "a randomly chosen number," or "a number chosen in such a way that all possible values are equally likely." There's no such thing as a single random number. I'd say that Snap ! did a better job in choosing numbers 1 to 10 randomly. Google's RNG choose the number 9 twice in a row, which doesn't tell me that it was randomly choosing numbers. Also the second one (Google) chose numbers 1 to 5 in different orders, which makes it basically make 5 number combinations.įor the 1 to 10 tests, the first one (Snap) chose numbers that were different every time, so no repetition or anything for us. I mean, the first random number generator chose 2 two times in a row, which would most likely conclude that it wasn't random at all. So let's just say that they likely did not choose random numbers. The second one, which used Google's RNG, decided to choose all the numbers, which deemed it useless. The first number generator, which used Snap !, chose to choose the numbers 2, 3, and 5. But they were given choices to choose numbers between 1 and 2, and so didn't really have options.įor the 1 to 5 tests, the test results were much different. So using 2 random number generators, I was able to depict if random number generators were really random or not, and here's the answer.įor the 1 to 2 tests, the tests were almost identical, and so let's just say that they likely didn't choose a random number. The first two attempts had the same number, which is weird. You can see that out of 5 attempts, 2 of these attempts were the same number, which was 9. The random number generator decided to choose all the numbers, which was either a coincidence, or on purpose. Welp, the results were different this time. Surprisingly, the results were almost identical! Then I could use these results to determine if random number generators REALLY are randomly generated. Now I will use another random number generator and see what its results would be, and then I can see whether the results would be the same or not. This time, the random number generator DIDN'T choose a number that is the same as a number it chose before. However, the RNG didn't choose numbers like 1 or 4, mainly prime numbers like 2, 3, and 5. ![]() You can see that out of 5 attempts, 2 attempts were of the same number, which was 3, and another 2 attempts were of the same number, which was 5. You can see that out of 5 attempts, 4 of these attempts were the same number, which was 1. Each number would randomly be chosen for 5 rounds. Then I put a number from 1 to 2, then 1 to 5, and then 1 to 10. So I'm thinking: Just how random can randomly picked numbers be?īy this I mean "What is the probability that a randomly picked number isn't random?" So let's do it!Īlright, I opened up the Snap! editor to play with the random number block. And then I thought about a unit I was learning in math that same day, which was about probability. Okay, so I was playing with a random number generator one day. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |