Re: Open Question - Is there an estimate for the amount of entropy in a random source with a normal distribution?

On Mon, 01 Dec 2003 14:54:40 GMT, Francois Panneton
<[EMAIL PROTECTED]> wrote:

>
>>> True random data has a uniform distribution.
>
>Data that does not follow a uniform distribution is not "truly" random ?
>

You can't really tell from a single sentence taken
out of context, but in this case, no.

"truly" random usually means non-deterministic,
or what I like to call "unreproducible".
But it can mean "completely" random, as in, "it's not
possible to predict the next value generated with an 
accuracy greater than chance."
In that sense, the sum of two dice isn't random,
because you can predict that 7 will happen more often.


--- begin paste of snippet http://www.helsbreth.org/random/ ---
 What does random mean: The three Uns.

 A true random number generator has three important properties:

   * it's Unbiased. All values of whatever sample size is 
     collected are equiprobable.
   * it's Unpredictable. It is impossible to predict what 
     the next output will be, given all the previous outputs, 
     but not the internal "hidden" state.
   * it's Unreproducible.  Two of the same generators, 
     given the same starting conditions, will produce 
     different outputs.

 Usually when a person says they have a "good" random 
 number generator, they mean it is unbiased. If they say 
 they have a "true" RNG, they usually mean it's unreproducible. 
 If they say it's "cryptographically strong" they mean 
 it's unpredictable. Very rarely do they mean it's all three UNs. 
 This isn't necessarily a bad thing, but it's worth remembering 
 when evaluating claims that one RNG is "better" than another.

--- end paste ---


Scott Nelson <[EMAIL PROTECTED]>