We use cookies to ensure you have the best browsing experience on our website. Please read our cookie policy for more information about how we use cookies.
  1. Prepare
  2. Tutorials
  3. 10 Days of Statistics
  4. Day 7: Pearson Correlation Coefficient I
  5. Discussions

Day 7: Pearson Correlation Coefficient I

  • razawy_h
     + 0 comments

    I am bit confused why its not mentioned to take the population standard deviation instead of the sample standarddeviation 

    # Enter your code here. Read input from STDIN. Print output to STDOUT
import math
import statistics
n = int(input())


X =list(map(float, input().split()))


Y =list(map(float, input().split()))
    

def calcpearsonCov(dataset1, dataset2):
    averagex= statistics.mean(dataset1)
    averagey = statistics.mean(dataset2)
    result = 0
    for i in range(0, len(dataset1)):
        result += (dataset1[i] - averagex) * (dataset2[i]- averagey)
    #result = result *(1/len(dataset1))
    stdevx = statistics.pstdev(dataset1)
    stdevy = statistics.pstdev(dataset2)
    result = result/(n*(stdevx*stdevy))
    return result
    
result = calcpearsonCov(X, Y)
print(round(result, 3))