// By Bell //examples from c++ reference guide recast in a class, to display random numbers generated on a distribution /* Coding Challenge Roll a dice and sum up the results until sum is > 12. Which is most likely result? a) Guess the answer b) Simulate that experiment and see the true result. (Maybe 1000 tries should do it) To calculate exactly without simulating is a bit tricky. But approximately we may assign the same probability to all outcomes from 7 to 12. Bonus: Calculate estimated average and most likely result by statistic methods. 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). UNIFORM integer distribution Random number distribution that produces integer values according to a uniform discrete distribution. This distribution produces random integers in a range [a,b] where each possible value has an equal likelihood of being produced. This is the distribution function that appears on many trivial random processes (like the result of rolling a die). */ #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<0)avg+=double(p[i]*i)/double(nrolls); if(p[i]>max){max=p[i]; mode=i; } cout<< string(p[i]*nstars/nrolls,'*')< 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)&&(number<10)) ++p[int(number)]; } cout < distribution(par1,par2); int p[10]={}; for (int i=0; i=0)&&(number<10)) ++p[number]; } cout < distribution(par1,par2); int p[25]={}; for (int i=0; i=0)&&(number<25)) ++p[number]; } cout < distribution(par1,par2); int p[25]={}; int co; for (int i=0; i1){number += distribution(generator); --co; } if ((number>=0)&&(number<=25)) ++p[number]; } cout < distribution(par1,par2); int p[25]={}; for (int i=0; i=0)&&(number<=25)) ++p[number]; } cout <12 ("< distribution(par1,par2); int p[25]={}; int temp; for (int i=0; i12)break; number=temp; } if ((number>=0)&&(number<=25)) ++p[int(number)]; } cout <

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