Question

The following code below must be able to run using linked list instead of using arrays

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#include

#include

using namespace std;

//Class for standard deviation

class stdDev

{

private:

       int max;

       double value[100];

       double mean;

public:

       double CalMean()

       {

              double sum = 0;

              for (int i = 0; i < max; i++)

                     sum += value[i];

              return (sum / max);

       }

       double CalVariane()

       {

              mean = CalMean();

              double temp = 0;

              for (int i = 0; i < max; i++)

              {

                     temp += (value[i] - mean) * (value[i] - mean);

              }

              return temp / max;

       }

       double CalSampleVar()

       {

              mean = CalMean(); //get mean

              double temp = 0;

              for (int i = 0; i < max; i++)

              {

                     temp += (value[i] - mean) * (value[i] - mean); //apply formula

              }

              return temp / (max - 1); //returns sample variance

       }

       int SetValues(double *p, int count)

       {

              if (count > 100)

                     return -1;

              max = count;

              for (int i = 0; i < count; i++)

                     value[i] = p[i];

              return 0;

       }

       double CalStdDev()//returns Standard deviation

       {

              return sqrt(CalVariane());

       }

       double SampleStdDev()//returns sample deviation

       {

              return sqrt(CalSampleVar());

       }

};

class Calculate

{

private:

       double XTerms[100];

       double YTerms[100];

       int max;

       stdDev x; // Standard deviation for x

       stdDev y;// Standard deviation for y

public:

       //set x and y series values to class members

       void SetValues(double *xval, double *yval, int count)

       {

              for (int i = 0; i < count; i++)

              {

                     XTerms[i] = xval[i];

                     YTerms[i] = yval[i];

              }

              x.SetValues(xval, count);

              y.SetValues(yval, count);

              max = count;

       }

       double Calculate_Covariance()

       {

              double xmean = x.CalMean();//Get X meam

              double ymean = y.CalMean();//get y mean

              double total = 0;

              for (int i = 0; i < max; i++)

              {

                     total += (XTerms[i] - xmean) * (YTerms[i] - ymean);

              }

              return total / max;//return Covariance

       }

       double Calculate_Correlation()//Find correlation

       {

              double cov = Calculate_Covariance();

              double correlation = cov / (x.CalStdDev() * y.CalStdDev());

              return correlation;

       }

};

int main()

{

       Calculate calc; //create object of class

       double xarr[] = { 0, 2, 4, 6, 8 }; // x series

       double yarr[] = { 6, 13, 15, 16, 20 };// y series

       calc.SetValues(xarr, yarr, sizeof(xarr) / sizeof(xarr[0]));//set series values

       cout << "X series ={ 0, 2, 4, 6, 8 }\nY series={ 6, 13, 15, 16, 20 }\n";

       cout << "\nCorrelation " << calc.Calculate_Correlation() << "\n\n";

       system("pause");

}

/*

       Output

X series ={ 0, 2, 4, 6, 8 }

Y series={ 6, 13, 15, 16, 20 }

Correlation 0.952157

Press any key to continue . . .

*/

Answer 1

#include<iostream.h>
#include<conio.h>
#include<math.h>
//Class for standard deviation
class stdDev
{
private:
int max;
double value[100];
double mean;
public:
double CalMean()
{
   double sum = 0;
   for (int i = 0; i < max; i++)
       sum += value[i];
   return (sum / max);
}
double CalVariane()
{
   mean = CalMean();
   double temp = 0;
   for (int i = 0; i < max; i++)
   {
       temp += (value[i] - mean) * (value[i] - mean);
   }
   return temp / max;
}
double CalSampleVar()
{
   mean = CalMean(); //get mean
   double temp = 0;
   for (int i = 0; i < max; i++)
   {
       temp += (value[i] - mean) * (value[i] - mean); //apply formula
   }
   return temp / (max - 1); //returns sample variance
}
int SetValues(double *p, int count)
{
   if (count > 100)
       return -1;
   max = count;
   for (int i = 0; i < count; i++)
       value[i] = p[i];
   return 0;
}
double CalStdDev()//returns Standard deviation
{
   return sqrt(CalVariane());
}
double SampleStdDev()//returns sample deviation
{
   return sqrt(CalSampleVar());
}
};
class Calculate
{
private:
double XTerms[100];
double YTerms[100];
int max;
stdDev x; // Standard deviation for x
stdDev y;// Standard deviation for y
public:
//set x and y series values to class members
void SetValues(double *xval, double *yval, int count)
{
   for (int i = 0; i < count; i++)
   {
       XTerms[i] = xval[i];
       YTerms[i] = yval[i];
   }
   x.SetValues(xval, count);
   y.SetValues(yval, count);
   max = count;
}
double Calculate_Covariance()
{
   double xmean = x.CalMean();//Get X meam
   double ymean = y.CalMean();//get y mean
   double total = 0;
   for (int i = 0; i < max; i++)
   {
       total += (XTerms[i] - xmean) * (YTerms[i] - ymean);
   }
   return total / max;//return Covariance
}
double Calculate_Correlation()//Find correlation
{
   double cov = Calculate_Covariance();
   double correlation = cov / (x.CalStdDev() * y.CalStdDev());
   return correlation;
}
};
int main()
{
clrscr();
Calculate calc; //create object of class
double xarr[] = { 0, 2, 4, 6, 8 }; // x series
double yarr[] = { 6, 13, 15, 16, 20 };// y series
calc.SetValues(xarr, yarr, sizeof(xarr) / sizeof(xarr[0]));//set series values
cout << "X series ={ 0, 2, 4, 6, 8 }\nY series={ 6, 13, 15, 16, 20 }\n";
cout << "\nCorrelation " << calc.Calculate_Correlation() << "\n\n";
cout<<("Press any key to continue");
getch();
}

DOSBox 0.74, Cpu speed: max 100% cycles, Frameskip 0, Program: TC- X series 0, 2, 4, 6, 8 series- 6, 13, 15, 16, 20 1 orrelation 0.952157 press any key to continue.. . .