Question

(JAVA)

Implement a ‘runnable’ Class called “NumericAnalyzer”. Here’s the functional behavior that must be implemented.

• NumericAnalyzer will accept a list of 1 or more numbers as command line arguments. These numeric values do not need to be ordered (although you’ll need to display these values sorted ascendingly). NOTE: Don’t prompt the user for input – this is an exercise passing values to your program via the command line!
• Error checking: if the user fails to pass in parameters, the program will display an error message (of your choice) and exit early.
• The main() method’s String [] args argument values must be converted and assigned to a numeric/integer array.
• Your program will display the following information about the numbers provided by the user:
  1. This list of numbers provided by the user sorted ascendingly.
  2. The size of number list (the number of numbers!)
  3. The average or mean value.
  4. The median - the middle value of the set of numbers sorted. (Simple Algorithm: index = the length of the array divided by 2).
  5. The min value.
  6. The max value.
  7. The sum
  8. The range: the difference between the max and min
  9. Variance: Subtract the mean from each value in the list. This gives you a measure of the distance of each value from the mean. Square each of these distances (and they’ll all be positive values), add all of the squares together, and divide that sum by the number of values (that is, take the average of these squared values) .
  10. Standard Deviation: is simply the square root of the variance.

Answer 1

Please find the below well-commented code:

Code text:

import java.util.*; import java.lang.*; class NumericAnalyzer {    void sortedList(int[] list){                                   //sorts the list        Arrays.sort(list);        System.out.print("User list sorted ascendingly: ");        for(int i = 0;i < list.length; i++)            System.out.print(list[i] + " ");                       //print the elements of list        System.out.print("\n");    }       void sizeOfTheList(int[] list){                                   //to print the size of the list        System.out.println("The Size of the List:"+list.length);    }       void averageOrMean(int[] list){                                   //prints average of the list        System.out.print("Average Value of the List:");        int sum=0;        for(int i = 0;i < list.length; i++)            sum=sum+list[i];                                       //calculate the sum        System.out.println((sum+0.0)/list.length);                   //print the median    }       void median(int[] list){        Arrays.sort(list);        System.out.print("The Median of the List:");                      System.out.println(list[list.length/2]);                   //Prints median    }       void min(int[] list){                                           //min element        Arrays.sort(list);        System.out.println("Minimum value of the list: " + list[0]);      }       void max(int[] list){                                           //max element        Arrays.sort(list);        System.out.println("Minimum value of the list: " + list[list.length-1]);    }       void sum(int[] list){                                           //print sum of the list        int sum=0;        for(int i = 0;i < list.length; i++)            sum=sum+list[i];        System.out.println("Sum of list is : " + sum);    }       void range(int[] list){                                           //print the range        Arrays.sort(list);        System.out.println("The range : " + (list[list.length] - list[0]));    }       void variance(int[] list){                                       //function to print the variance        Arrays.sort(list);        int sum=0,squaredSum = 0;        for(int i = 0;i < list.length; i++)            sum=sum+list[i];               int mean = sum/list.length;               for(int i = 0;i < list.length;i++){            list[i] = list[i] - mean;            list[i] = list[i]*list[i];            squaredSum = squaredSum + list[i];                       //calculate the squared sum        }               System.out.println("The variance : "+ ((squaredSum+(0.0))/list.length));   //print the variance    }       void standardDeviation(int[] list){                               //function to print the variance        Arrays.sort(list);        int sum=0,squaredSum = 0;        for(int i = 0;i < list.length; i++)                                      sum=sum+list[i];               int mean = sum/list.length;               for(int i = 0;i < list.length;i++){            list[i] = list[i] - mean;            list[i] = list[i]*list[i];            squaredSum = squaredSum + list[i];        }        double variance = (squaredSum+0.0)/list.length;                                 System.out.println("Standard Deviation: " + Math.sqrt(variance));   //print the squared sum    } } public class NumericAnalyzerMain{    public static void main(String [] args){        if(args.length == 0){            System.out.println("ERROR****Please pass in some arguments\n");   //error if no command line args            System.exit(1);        }               int [] list = new int[args.length];               try{                                                               //will raise error if command line args is not            for(int i = 0; i < args.length; i++){                           //integer                list[i] = Integer.parseInt(args[i]);                              }        }        catch (NumberFormatException nfe) { System.out.println("The argument must be an integer/numeric."); System.exit(1); }               NumericAnalyzer numericAnalyzer = new NumericAnalyzer();           //instance of NumericAnalyzer               //call the individual methods               numericAnalyzer.sortedList(list);               numericAnalyzer.sizeOfTheList(list);               numericAnalyzer.averageOrMean(list);               numericAnalyzer.median(list);               numericAnalyzer.min(list);               numericAnalyzer.max(list);               numericAnalyzer.sum(list);               numericAnalyzer.variance(list);               numericAnalyzer.standardDeviation(list);    } }

Output: