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:

since it can be assumed that what aslam is making is a template by compiling all the commonly used excel formatting in several worksheets in an excel document, aslam can choose to save it using the .xltx or .xltm format instead. thus, aslam can distribute the templates he has made to his team members in an easier manner.

so much for the extra points :