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    <p>Well, if you seed both <code>Random</code> instances with the same value, you will definitely not get quality discrete uniform distribution. Consider the most basic case, which literally prints the exact same number twice (doesn't get much less random than that ...):</p> <pre><code>public class RngTest2 { public static void main(String[] args) throws Exception { long currentTime = System.currentTimeMillis(); Random r1 = new Random(currentTime); Random r2 = new Random(currentTime); System.out.println(r1.nextInt()); System.out.println(r2.nextInt()); } } </code></pre> <p>But that's just a single iteration. What happens if we start cranking up the sample size?</p> <p>Here is a scatter plot of a distribution from running two same-seeded RNGs side-by-side to generate 2000 numbers total:</p> <p><img src="https://i.stack.imgur.com/7kIyO.jpg" alt="alt text"></p> <p>And here is a distribution of running a single RNG to generate 2000 numbers total:</p> <p><img src="https://i.stack.imgur.com/9402v.jpg" alt="alt text"></p> <p>It seems pretty clear which approach produced higher quality discrete uniform distribution over this finite set.</p> <p>Now almost everyone knows that seeding two RNGs with the same seed is a bad idea if you're looking for high quality randomness. But this case does make you stop and think: we <em>have</em> created a scenario where each RNG is independently emitting fairly high quality randomness, but when their output is combined it is notably lower in quality (less discrete.)</p>
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    1. POUniform distribution with Random
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    1. USMike Clark
    1. USMike Clark
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    1. COYou answer a question with a question.
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      1. USDavid Larochette
    2. COyou are right, but note that even in this case, the resulting distribution **is** uniform.
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      1. USGrodriguez
    3. CO@Grodriguez the plot may be misleading - remember that on the first scatter plot, each point is actually 2 points overlapping exactly. Visually, chart 1 appears uniform just with fewer samples than chart 2. But in fact both charts have the same number of samples -- the first less randomly placed than the second. At least, that's how I think of it. I wonder what the Chi Squared Test would say about the output.
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      1. USMike Clark
 

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