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I was going to post this question on SO but I suspect it needs mathematical treatment. I need to make a decision(True or False) while running a simulation and I decided that this particular decision should be random.
At first I compared a random value with a static value (0.5) but I soon realized that I am getting 50% True, and 50% False. (So I can use 0.75 if I want 75% True and 25% False)
But I didn't want this particular distribution. So I wrote a function which compared a random value (between 0 and 1) with another random value.
[I have taken care of seeding the random generator with microseconds so IMO 'seed'ing part is not the problem.]
The function looks like

getResponse() {
    rand1 = rand();
    rand2 = rand();
    if ( rand1 > rand2 )
        return True;
        return False;

My question is how random is the outcome of this function?
Here is the outcome (1=True 0=False) for 100 calls to function
Do you see any pattern? Should there be any pattern? What happens if I reseed the random generator after say every 3rd call?
If this approach doesn't look right, can you suggest any other approach?


I have realized my mistake of confusing pattern and distribution. I apologize for the same. I must understand first what distribution I want . Unless that is taken care of, I can not make any progress.
After going through comments and suggestions, I feel that a functional approach will either require keeping track of past results or decide on the distribution of outcome.
On second thoughts I decided neither is necessary if we get a constantly changing variable into the picture.
Enter microtime() which returns microseconds after current second.
Too bad I can't answer till next 8 hours, so I am excusing myself to type it here.

getResponse() {
    return ( microtime()*1000000 % 2 ) ? True : False;
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The probability of getting True is still 1/2. – Florian Aug 25 '11 at 7:13
What distribution DO you want? – Ricky Demer Aug 25 '11 at 7:16
So, the question should be: Does the quality improve if one compares two random numbers instead of comparing one random number to 1/2. I can't think of any reason why this should be true, but I can think of one why the quality can get worse: the cycle length decreases to one half of the original one. – Florian Aug 25 '11 at 7:31
@Sudhi - what do you mean by random then? I'm unclear what you are trying to achieve. – Mark Bennet Aug 25 '11 at 7:43
Maybe you want the probability of getting True to be fixed the start of each simulation. So, at the start, somehow determine a number p, and getResponse becomes { return rand() <= p; } Is this what you want? I'm just guessing wildly. – Florian Aug 25 '11 at 8:41
up vote 1 down vote accepted

Use or

When there have been m falses and n trues,
return false with probability (n+1)/(m+1+n+1) and true with probability (m+1)/(m+1+n+1).

share|cite|improve this answer
thanks for your answer, it does seem a good option but I am not so keen on it as it entails keeping track of past results, which I don't want. How about this (see my answer below) – Sudhi Aug 25 '11 at 9:53
darn! cant answer, here is the short of it. microtime() returns time in microseconds after the current second. So getResponse() { return ( microtime()*1000000 % 2 ); }. What do you think about it? – Sudhi Aug 25 '11 at 10:00
That would not be "(truly) randomly". – Ricky Demer Aug 25 '11 at 10:02
can you please elaborate on it? – Sudhi Aug 25 '11 at 10:09
Also, using a RNG like 'time mod 2' is a dangerously bad idea. Most notably, many systems will not return those sorts of values with as much precision as you'd expect; I've seen multiple systems where the 'time in microseconds' value is always a multiple of 2 - in fact, always a multiple of 10! I strongly discourage using anything like this, and encourage some further study of what randomness means, because I think you're still somewhat confused on the core principles. – Steven Stadnicki Aug 25 '11 at 17:05

protected by MJD Nov 5 '15 at 23:34

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