Write a test client for Randomthat checks that two methods, namely, nextGaussian()and nextLong()in the library operate as expected. Take a command-line argument N, generate Nrandom numbers using each of the methods in Random, and print out their mean, and standard deviation.

Part 2: Implement a class that extends Random with a static method maxwellBoltzmann() that returns a random value drawn from a Maxwell-Boltzmann distribution with parameter s. To produce such a value, return the square root of the sum of the squares of three Gaussian random variables with mean 0 and standard deviation s. The speeds of molecules in an ideal gas have a Maxwell-Boltzmann distribution. Write a test client to test this new method, taking as command-line arguments N and sand prints N random numbers from the Maxwell Boltzmann distribution with parameter s.

/ TestRandom.java

import java.util.Random;

public class TestRandom {

   // method to find the mean value of set of numbers

   // using Number as data type, so that it can represent both Double and Long

   // types needed for this program

   static double calculateMean(Number array[]) {

        double sum = 0;

        // summing values

        for (int i = 0; i < array.length; i++) {

            sum += array[i].doubleValue();

        }

        // finding average and returning it

        double avg = (double) sum / array.length;

        return avg;

   }

   // method to find the standard deviation value of set of numbers

   // using Number as data type, so that it can represent both Double and Long

   // types needed for this program

   static double calculateSD(Number array[], double mean) {

        // initializing sum of squared difference between each number and mean

        // to 0

        double sumSquaredDiff = 0;

        // looping

        for (int i = 0; i < array.length; i++) {

            // finding difference between current number and mean, squaring the

            // result, adding to sumSquaredDiff

            sumSquaredDiff += Math.pow(array[i].doubleValue() - mean, 2);

        }

        // finding variance

        double variance = (double) sumSquaredDiff / array.length;

        // finding square root of variance as standard deviation

        double sd = Math.sqrt(variance);

        return sd;

   }

   public static void main(String[] args) {

        // if no command line arguments given, displaying usage and quit

        if (args.length == 0) {

            System.out.println("Usage: java TestRandom <n>");

            System.exit(0);

        }

        // parsing first argument as integer N

        int N = Integer.parseInt(args[0]);

        // declaring a Double array and a Long array of size N

        Double gaussian[] = new Double[N];

        Long lng[] = new Long[N];

        // Random number generator

        Random random = new Random();

        // looping for N times

        for (int i = 0; i < N; i++) {

            // generating a guassian number, adding to array

            gaussian[i] = random.nextGaussian();

            // generating a long number, adding to array

            lng[i] = random.nextLong();

        }

        // finding average and standard deviation of both array values, we can

        // use the same functions for both types

        double avgGaussian = calculateMean(gaussian);

        double sdGaussian = calculateSD(gaussian, avgGaussian);

        double avgLong = calculateMean(lng);

        double sdLong = calculateSD(lng, avgLong);

        // displaying mean and standard deviation of both, formatted to 2 digits

        // after decimal point. the gaussian values will yeild a mean value

        // close to 0 and a standard deviation close to 1

        System.out.printf("Mean of %d gaussian values: %.2f\n", N, avgGaussian);

        System.out.printf("Standard deviation: %.2f\n", sdGaussian);

        System.out.printf("Mean of %d long values: %.2f\n", N, avgLong);

        System.out.printf("Standard deviation: %.2f\n", sdLong);

   }

}

Explanation:

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