open(INPUT,"ZScoreKMV.csv") or die "Can't open file: $!\n";
open(outfile, ">pairwiseArray");

@X;
@Y;

while ( $line = <INPUT> ) {
	($X[$i],$Y[$i]) = split(/,/, $line);
	chop($Y[$i]);

	$i++
}

$n=$i;
$SumX=0;
$SumY=0;

#Calculating the mean

for($i=0;$i<$n; $i++){
$SumX += $X[$i];
$SumY += $Y[$i];
}

$MeanX = $SumX/$n;
$MeanY = $SumY/$n;

#Calculating Std Deviation for X & Y

$XiSquareSum = 0;
for($i=0;$i<$n;$i++){
$Xi = $X[$i] - $MeanX;
$XiSquare = $Xi*$Xi;
$XiSquareSum += $XiSquare; 
}
$VarianceX = $XiSquareSum/$n ;
$StdDevX = sqrt($VarianceX);

$YiSquareSum = 0;x
for($i=0;$i<$n;$i++){
$Yi = $Y[$i] - $MeanY;
$YiSquare = $Yi*$Yi;
$YiSquareSum += $YiSquare; 
}
$VarianceY = $YiSquareSum/$n ;
$StdDevY = sqrt($VarianceY);

#Calculate the covariance between X & Y
$CovSum=0;
for($i=0;$i<$n;$i++){
$Xi = $X[$i] - $MeanX;
$Yi = $Y[$i] - $MeanY;
$Covi = $Xi*$Yi;
$CovSum += $Covi;
}
$Covariance = $CovSum/$n;

#print("Mean X= $MeanX \n");
#print("Mean Y= $MeanY \n");
#print("STD X= $StdDevX \n");
#print("STD Y= $StdDevY \n");
#Calculate the correlation coefficient
$r = $Covariance/($StdDevX*$StdDevY);

print outfile "The correlation coefficient is $r \n";