# import statistics as stat
from sys import stdin, stdout
import math

def mean(arr):
    return sum(arr) / len(arr)

def sd(arr, mean):
    squared_diff_sum = sum((x - mean)**2 for x in arr)
    variance = squared_diff_sum / len(arr)
    return math.sqrt(variance)

def covariance(X, Y):
    mean_X = mean(X)
    mean_Y = mean(Y)
    covariance_sum = sum((X[i] - mean_X) * (Y[i] - mean_Y) for i in range(len(X)))
    cov = covariance_sum / len(X)
    return cov

def pearson_correlation(X, Y):
    cov_XY = covariance(X, Y)
    st_dev_X = sd(X, mean(X))
    st_dev_Y = sd(Y, mean(Y))
    coefficient = cov_XY / (st_dev_X * st_dev_Y)
    return coefficient

n = int(stdin.readline().strip())
X = list(map(float, stdin.readline().strip().split()))
Y = list(map(float, stdin.readline().strip().split()))

if len(X) != len(Y):
    print("Error: Data sets X and Y must have equal lengths")
else:
    t = pearson_correlation(X, Y)
    print(round(t, 3))