How to write a C program to find the Covariance and Correlation.
C code to find Covariance and Correlation
#include <stdio.h>
#include <math.h>
class StdDeviation
{
private:
int max;
double value[100];
double mean;
public:
double CalculateMean()
{
double sum = 0;
for(int i = 0; i < max; i++)
sum += value[i];
return (sum / max);
}
double CalculateVariane()
{
mean = CalculateMean();
double temp = 0;
for(int i = 0; i < max; i++)
{
temp += (value[i] - mean) * (value[i] - mean) ;
}
return temp / max;
}
double CalculateSampleVariane()
{
mean = CalculateMean();
double temp = 0;
for(int i = 0; i < max; i++)
{
temp += (value[i] - mean) * (value[i] - mean) ;
}
return temp / (max - 1);
}
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 Calculate_StandardDeviation()
{
return sqrt(CalculateVariane());
}
double Calculate_SampleStandardDeviation()
{
return sqrt(CalculateSampleVariane());
}
};
class FinanceCalculator
{
private:
double XSeries[100];
double YSeries[100];
int max;
StdDeviation x;
StdDeviation y;
public:
void SetValues(double *xvalues, double *yvalues, int count)
{
for(int i = 0; i < count; i++)
{
XSeries[i] = xvalues[i];
YSeries[i] = yvalues[i];
}
x.SetValues(xvalues, count);
y.SetValues(yvalues, count);
max = count;
}
double Calculate_Covariance()
{
double xmean = x.CalculateMean();
double ymean = y.CalculateMean();
double total = 0;
for(int i = 0; i < max; i++)
{
total += (XSeries[i] - xmean) * (YSeries[i] - ymean);
}
return total / max;
}
double Calculate_Correlation()
{
double cov = Calculate_Covariance();
double correlation = cov / (x.Calculate_StandardDeviation() * y.Calculate_StandardDeviation());
return correlation;
}
};
int main()
{
FinanceCalculator calc;
{
printf("\n\nZero Correlation and Covariance Data Set\n");
double xarr[] = { 8, 6, 4, 6, 8 };
double yarr[] = { 10, 12, 14, 16, 18 };
calc.SetValues(xarr,yarr,sizeof(xarr) / sizeof(xarr[0]));
printf("Covariance = %.10lf\n", calc.Calculate_Covariance());
printf("Correlation = %.10lf\n", calc.Calculate_Correlation());
}
{
printf("\n\nPositive Correlation and Low Covariance Data Set\n");
double xarr[] = { 0, 2, 4, 6, 8 };
double yarr[] = { 6, 13, 15, 16, 20 };
calc.SetValues(xarr,yarr,sizeof(xarr) / sizeof(xarr[0]));
printf("Covariance = %.10lf\n", calc.Calculate_Covariance());
printf("Correlation = %.10lf\n", calc.Calculate_Correlation());
}
{
printf("\n\nNegative Correlation and Low Covariance Data Set\n");
double xarr[] = { 8, 6, 4, 2, 0 };
double yarr[] = { 6, 13, 15, 16, 20 };
calc.SetValues(xarr,yarr,sizeof(xarr) / sizeof(xarr[0]));
printf("Covariance = %.10lf\n", calc.Calculate_Covariance());
printf("Correlation = %.10lf\n", calc.Calculate_Correlation());
}
{
printf("\n\nPositive Correlation and High Covariance Data Set\n");
double xarr[] = { 8, 6, 4, 2, 0 };
double yarr[] = { 1006, 513, 315, 216, 120 };
calc.SetValues(xarr,yarr,sizeof(xarr) / sizeof(xarr[0]));
printf("Covariance = %.10lf\n", calc.Calculate_Covariance());
printf("Correlation = %.10lf\n", calc.Calculate_Correlation());
}
{
printf("\n\nNegative Correlation and High Covariance Data Set\n");
double xarr[] = { 8, 6, 4, 2, 0 };
double yarr[] = { 120, 216, 315, 513, 1006 };
calc.SetValues(xarr,yarr,sizeof(xarr) / sizeof(xarr[0]));
printf("Covariance = %.10lf\n", calc.Calculate_Covariance());
printf("Correlation = %.10lf\n", calc.Calculate_Correlation());
}
}
Write a C program to find Correlation
#include <stdio.h>
#include <math.h>
int main() {
int x[100], y[100], xy[100], xsquare[100], ysquare[100];
int i, n, xsum, ysum, xysum, xsqr_sum, ysqr_sum;
float coeff, num, deno;
xsum = ysum = xysum = xsqr_sum = ysqr_sum = 0;
/* get the number of entries from the user */
printf("Enter the value for n:");
scanf("%d", &n);
/* get the values for x and y from the user */
printf("Enter the value for x and y:\n");
for (i = 0; i < n; i++) {
printf("x[%d] and y[%d]: ", i, i);
scanf("%d%d", &x[i], &y[i]);
}
/* find the needed data to manipulate correlation coeff */
for (i = 0; i < n; i++) {
xy[i] = x[i] * y[i];
xsquare[i] = x[i] * x[i];
ysquare[i] = y[i] * y[i];
xsum = xsum + x[i];
ysum = ysum + y[i];
xysum = xysum + xy[i];
xsqr_sum = xsqr_sum + xsquare[i];
ysqr_sum = ysqr_sum + ysquare[i];
}
num = 1.0 * ((n * xysum) - (xsum * ysum));
deno = 1.0 * ((n * xsqr_sum - xsum * xsum)* (n * ysqr_sum - ysum * ysum));
/* calculate correlation coefficient */
coeff = num / sqrt(deno);
/* print the result */
printf("Correlation Coefficient : %.4f\n", coeff);
return 0;
}
