// By Bell //examples from c++ reference guide recast in a class, to display random numbers generated on a distribution /* NORMAL or Gaussian distribution with mean m and standard deviation s CHI SQUARED distribution with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables. the BINOMIAL distribution with parameters n and p is the discrete probability distribution of the number of successes in a sequence of n independent experiments, each asking a yes–no question, and each with its own boolean-valued outcome: success/yes/true/one (with probability p) or failure/no/false/zero (with probability q = 1 − p). */ #include #include #include #include using namespace std; class randomDist{ public: double par1, par2; //parameters for the distribution const int nrolls=10000; // number of experiments const int nstars=100; // maximum number of stars to distribute // Constructor Initializes a distribution object randomDist(double m, double s=1.):par1(m), par2(s){ if (s < 0) { cout << "Warning: negative value will upset distribution\n"; par2 = 0.01;} } // Method to print any distribution int printDist(int nstars,int nrolls,int p[]){ for (int i=0; i<10; ++i) { cout << i << "-" << (i+1) << ": "; if(i<9)cout<<" "; cout << string(p[i]*nstars/nrolls,'*') << endl;} cout< distribution(par1,par2); int p[10]={}; for (int i=0; i=0.0)&&(number<10.0)) ++p[int(number)]; } cout << "normal_distribution ("< distribution(par1); int p[10]={}; for (int i=0; i=0.0)&&(number<10.0)) ++p[int(number)]; } cout < distribution(par1,par2); int p[10]={}; for (int i=0; i=0.0)&&(number<10.0)) ++p[int(number)]; } cout <

distributionClass