C++ program to implement correlation analysis on nominal and numeric data type.

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Simple C++ program to implement correlation analysis on nominal and numeric data type.


Code:


#include<iostream>

#include<math.h>

using namespace std;

int main() {

int n1, i, sum=0, sum1=0;

floatmean_A, mean_B, std_A, std_B, corr;

cout<< "Enter the number of data: " <<endl;

cin>> n1;

int x[n1];

cout<< "Enter the data for A: " <<endl;

for(i=0; i<n1; i++) {

cin>> x[i]; }

int y[n1];

cout<< "Enter the data for B: " <<endl;

for(i=0; i<n1; i++) {

cin>> y[i]; }

for(i=0; i<n1; i++) {

sum = sum + x[i];

sum1 = sum1 + y[i]; }

mean_A = (float)sum / n1;

mean_B = (float)sum1 / n1;

sum=0;

sum1=0;

for(i=0; i<n1; i++) {

sum = sum + pow(x[i] - mean_A, 2);

sum1 = sum1 + pow(y[i] - mean_B, 2); }

std_A = sqrt(sum / n1);

std_B = sqrt(sum1 / n1);

sum=0;

for(i=0; i<n1; i++) {

sum = sum + x[i] * y[i]; }

corr = ((sum - (n1 * mean_A * mean_B))/(n1 * std_A * std_B));

if(corr> 0) {

cout<< "A and B are positively correlated." <<endl; }

else if(corr< 0) {

cout<< "A and B are negatively correlated." <<endl; }

else if(std_A == 0 || std_B == 0) {

cout<< "Correlation is undefined." <<endl; }

else {

cout<< "A and B are independent." <<endl; }

return 0;

}

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