Pearson Correlation Coefficient

The Pearson correlation coefficient is a measure of how highly correlated two variables are. It is a value between 1 and −1, where 1 indicates that the variables are perfectly correlated, 0 indicates no correlation, and −1 means they are perfectly inversely correlated.

Figure B-2 shows the Pearson correlation coefficient.

This can be implemented with the following code:

def pearson(x,y):
  n=len(x)
  vals=range(n)

  # Simple sums
  sumx=sum([float(x[i]) for i in vals])
  sumy=sum([float(y[i]) for i in vals])

  # Sum up the squares
  sumxSq=sum([x[i]**2.0 for i in vals])
  sumySq=sum([y[i]**2.0 for i in vals])

  # Sum up the products
  pSum=sum([x[i]*y[i] for i in vals])

  # Calculate Pearson score
  num=pSum-(sumx*sumy/n)
  den=((sumxSq-pow(sumx,2)/n)*(sumySq-pow(sumy,2)/n))**.5
  if den==0: return 1

  r=num/den

  return r