non-uniform-distribution

In the example Josh gives of the flawed random method that generates a positive random number with a given upper bound n , I don't understand the two of the flaws he states. The method from the book is: private static final Random rnd = new Random(); //Common but deeply flawed static int random(int n) { return Math.abs(rnd.nextInt()) % n; } He says that if n is a small power of 2, the sequence of random numbers that are generated will repeat itself after a short period of time. Why is this the case? The documentation for Random.nextInt() says Returns the next pseudorandom, uniformly

From this question: Random number generator which gravitates numbers to any given number in range? I did some research since I've come across such a random number generator before. All I remember was the name "Mueller", so I guess I found it, here: Box-Mueller transform I can find numerous implementations of it in other languages, but I can't seem to implement it correctly in C#. This page, for instance, The Box-Muller Method for Generating Gaussian Random Numbers says that the code should look like this (this is not C#): #include <stdio.h> #include <stdlib.h> #include <math.h> #include <time

How can I create a random integer n in Java, between 1 and k with a "linear descending distribution", i.e. 1 is most likely, 2 is less likely, 3 less likely, ..., k least likely, and the probabilities descend linearly, like this: I know that there are dosens of threads on this topic already, and I apologize for making a new one, but I can't seem to be able to create what I need from them. I know that using import java.util.*; , the code Random r=new Random(); int n=r.nextInt(k)+1; creates a random integer between 1 and k , distributed uniformly. GENERALIZATION: Any hints for creating an