If a computer can only do determined things how can it make random numbers?
397527
Random numbers generated by a computer are not truly random but are generated by a complicated algorithm that makes numbers that appear to be random but aren't. An interesting discussion of this is available at the website listed below. Look for the Numb3rs Activity: Creating Random Numbers from September 30.
708244
It's random based on a computer generated choice.  No one knows.
551109
Try arranging them into an order that makes sense! Sometimes it could even be random.\n\nCryptology my Boy! Cryptology!\n\nGood Luck!
748551
Dude, I don't know anything about that button but i do know that every 108 minutes the buttons must be used to put the numbers in the computer or else the world ends. Also..just press the button and see what happens. Knowledge is power. Can I get a witness?
918201
isnt that what a computer do?
141533
I think you are asking about ALGORITHM:\nan algorithm is a logical recipe for performing some operation by the computer.
1064558
It is just a program with some artificial intelligence. It is programmed by any programmers to give random answers trying to scare you. Nothing to worry about.
767048
Random chances are the same as probabilities. If you are so interested, you should look into Quantum Theory. It describes it in depth.
370480
If you want to generate random numbers, almost every programming language I've ever come across has some function to generage the same sequence of random numbers every time. \nHope that helps.
84626
There is a random knowledge generator here...\n\nhttp://www.madsci.org/random.html
4160
Random discrete variables are specific numbers.  E.g., all integers X such that 1<= X <= 6.\nX can be 1, 2, 3, 4, 5, or 6\nThe probability that X=1 is 1/6.\n\nRandom continuous variables can be any of an infinite set of numbers in a range.  E.g., all X such that  1 < X < 6\nX can be any of an infinite set of numbers between 1 and 6.\nThe probability that X is any specific number is infinitesimal.
760690
=RAND() A random number between 0 and 1 (varies) \n=RAND()*100 A random number greater than or equal to 0 but less than 100 (varies) \n\nTo generate a random real number between a and b, use: \nRAND()*(b-a)+a
577182
Randomality is always an interesting topic from a computer science standpoint.  Check out this excerpt from wikipedia:\n\n"What constitutes a "true" random number is often difficult to decide, since the concept of randomness is itself somewhat difficult to define. What is universally agreed is that any "random number generator" based solely on deterministic computation cannot be regarded as a "true" random number generator, since its output is inherently predictable. John von Neumann once famously said "Anyone who uses software to produce random numbers is in a state of sin" (some sources say "arithmetic methods" instead of "software")."\n\nhttp://en.wikipedia.org/wiki/Random_number_generator
560819
well entropy is the measure of the randomness of the particles in question.
1006176
Generating a Pseudo-Random Number Sequence\n\n#include <stdio.h>\n#include <stdlib.h>\n...\n    long count, i;\n    char *keystr;\n    int elementlen, len;\n    char c;\n...\n/* Initial random number generator. */\n    srand(1);\n\n    /* Create keys using only lowercase characters */\n    len = 0;\n    for (i=0; i<count; i++) {\n        while (len < elementlen) {\n            c = (char) (rand() % 128);\n            if (islower(c))\n                keystr[len++] = c;\n        }\n\n        keystr[len] = '&#92;0';\n        printf("%s Element%0*ld&#92;n", keystr, elementlen, i);\n        len = 0;\n    }\n\n\nGenerating the Same Sequence on Different Machines\n\nstatic unsigned long next = 1;\nint myrand(void)  /* RAND_MAX assumed to be 32767. */\n{\n    next = next * 1103515245 + 12345;\n    return((unsigned)(next/65536) % 32768);\n}\n\nvoid mysrand(unsigned seed)\n{\n    next = seed;\n}\n\n\nRATIONALE\n\nThe ISO C standard rand() and srand() functions allow per-process pseudo-random streams shared by all threads. Those two functions need not change, but there has to be mutual-exclusion that prevents interference between two threads concurrently accessing the random number generator.\n\nWith regard to rand(), there are two different behaviors that may be wanted in a multi-threaded program:\n\nA single per-process sequence of pseudo-random numbers that is shared by all threads that call rand()\n\nA different sequence of pseudo-random numbers for each thread that calls rand()\n\nThis is provided by the modified thread-safe function based on whether the seed value is global to the entire process or local to each thread.\n\nThis does not address the known deficiencies of the rand() function implementations, which have been approached by maintaining more state. In effect, this specifies new thread-safe forms of a deficient function.
1030606
Randome Access Memory
911428
It's always "possible".  For example, trial division by progressively larger numbers, skipping multiples of 2 and 3, is the worst algorithm known, but it will get there eventually.\n\nEven the best algorithms known take longer and longer as the number gets bigger.  The records, which took several months on a cluster of machines, are for numbers around 200 digits.  I think each additional three digits makes these methods take about twice as long.  They use very very deep number theory.