C++ Program to Linear Fit the data using Least Squares Method

//Linear Fit
using namespace std;
int main()
    int i,j,k,n;
    cout<<"\nEnter the no. of data pairs to be entered:\n";        //To find the size of arrays
    double x[n],y[n],a,b;
    cout<<"\nEnter the x-axis values:\n";                //Input x-values
    for (i=0;i<n;i++)
    cout<<"\nEnter the y-axis values:\n";                //Input y-values
    for (i=0;i<n;i++)
    double xsum=0,x2sum=0,ysum=0,xysum=0;                //variables for sums/sigma of xi,yi,xi^2,xiyi etc
    for (i=0;i<n;i++)
        xsum=xsum+x[i];                        //calculate sigma(xi)
        ysum=ysum+y[i];                        //calculate sigma(yi)
        x2sum=x2sum+pow(x[i],2);                //calculate sigma(x^2i)
        xysum=xysum+x[i]*y[i];                    //calculate sigma(xi*yi)
    a=(n*xysum-xsum*ysum)/(n*x2sum-xsum*xsum);            //calculate slope
    b=(x2sum*ysum-xsum*xysum)/(x2sum*n-xsum*xsum);            //calculate intercept
    double y_fit[n];                        //an array to store the new fitted values of y    
    for (i=0;i<n;i++)
        y_fit[i]=a*x[i]+b;                    //to calculate y(fitted) at given x points
    for (i=0;i<n;i++)
        cout<<i+1<<"."<<setw(8)<<x[i]<<setw(15)<<y[i]<<setw(18)<<y_fit[i]<<endl;//print a table of x,y(obs.) and y(fit.)    
    cout<<"\nThe linear fit line is of the form:\n\n"<<a<<"x + "<<b<<endl;        //print the best fit line
    return 0;


Explanation of the code:

PhD researcher at Friedrich-Schiller University Jena, Germany. I'm a physicist specializing in theoretical, computational and experimental condensed matter physics. I like to develop Physics related apps and softwares from time to time. Can code in most of the popular languages. Like to share my knowledge in Physics and applications using this Blog and a YouTube channel.
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