Bernoulli Distribution in Data Structures

The Bernoulli Distribution is a discrete distribution having two possible outcomes labeled by x = 0 and x = 1. The x = 1 is success, and x = 0 is failure. Success occurs with probability p, and failure occurs with probability q as q = 1 – p. So

$$P\lgroup x\rgroup=\begin{cases}1-p\:for & x = 0\p\:for & x = 0\end{cases}$$

This can also be written as −

$$P\lgroup x\rgroup=p^{n}\lgroup1-p\rgroup^{1-n}$$

Example

 Live Demo

#include <iostream> #include <random> using namespace std; int main(){    const int nrolls=10000;    default_random_engine generator;    bernoulli_distribution distribution(0.7);    int count=0; // count number of trues    for (int i=0; i<nrolls; ++i)       if (distribution(generator))       count++;    cout << "bernoulli_distribution (0.7) x 10000:" << endl;    cout << "true: " << count << endl;    cout << "false: " << nrolls-count << endl; }

Output

bernoulli_distribution (0.7) x 10000: true:7024 false: 2976