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copied!<p>You should update the question to make clear what's exactly your use case.</p> <p>According to your comment, you shouldn't be using normal distribution at all. Instead try one of many <em>discrete</em> distributions, since you want integers at the end. There are a lot of those, but I'd recommend one - very simple. It uses <a href="http://en.wikipedia.org/wiki/Stochastic_vector" rel="nofollow noreferrer">stochastic vector</a> as the discrete probability distribution.</p> <p>Here's example implementation:</p> <pre><code>public class DiscreteRandom { private final double[] probDist; public DiscreteRandom(double... probs) { this.probDist = makeDistribution(probs); } private double[] makeDistribution(double[] probs) { double[] distribution = new double[probs.length]; double sum = 0; for (int i = 0; i < probs.length; i++) { sum += probs[i]; distribution[i] = sum; } return distribution; } public int nextInt() { double rand = Math.random(); int i = 0; while (rand > probDist[i]) i++; return i; } /** * Simple test */ public static void main(String[] args) { // We want 0 to come 3 times more often than 1. // The implementation requires normalized probability // distribution thus testProbs elements sum up to 1.0d. double[] testProbs = {0.75d, 0.25d}; DiscreteRandom randGen = new DiscreteRandom(testProbs); // Loop 1000 times, we expect: // sum0 ~ 750 // sum1 ~ 250 int sum0 = 0, sum1 = 0, rand; for (int i = 0; i < 1000; i++) { rand = randGen.nextInt(); if (rand == 0) sum0++; else sum1++; } System.out.println("sum0 = " + sum0 + "sum1 = " + sum1); } } </code></pre>

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