import itertools,math,numpy as np

def I(): return int(eval(input()))

def LI(): return list(map(int,input().split()))

N = I()

xy = np.array([LI() for _ in range(N)])

sum_norm = 0

dict_norm = {}

for a in itertools.permutations(list(range(N))):

    for i in range(len(a)-1):

        vector = xy[a[i+1]]-xy[a[i]]

        if not tuple(vector) in dict_norm:

            dict_norm[tuple(vector)] = np.linalg.norm(vector)

        sum_norm += dict_norm[tuple(vector)]

print((sum_norm/math.factorial(N)))

import itertools,math,numpy as np

def I(): return int(eval(input()))

def LI(): return list(map(int,input().split()))

N = I()

xy = np.array([LI() for _ in range(N)])

sum_norm = 0

dict_norm = {}

for a in itertools.permutations(list(range(N))):

    for i in range(len(a)-1):

        vector = tuple(xy[a[i+1]]-xy[a[i]])

        if not vector in dict_norm:

            dict_norm[vector] = np.linalg.norm(vector)

        sum_norm += dict_norm[vector]

print((sum_norm/math.factorial(N)))

import itertools, math, numpy as np


def I():
    return int(eval(input()))


def LI():
    return list(map(int, input().split()))


N = I()
xy = np.array([LI() for _ in range(N)])
sum_norm = 0
dict_norm = {}
for a in itertools.permutations(list(range(N))):
    for i in range(len(a) - 1):
        vector = xy[a[i + 1]] - xy[a[i]]
        if not tuple(vector) in dict_norm:
            dict_norm[tuple(vector)] = np.linalg.norm(vector)
        sum_norm += dict_norm[tuple(vector)]
print((sum_norm / math.factorial(N)))

import itertools, math, numpy as np


def I():
    return int(eval(input()))


def LI():
    return list(map(int, input().split()))


N = I()
xy = np.array([LI() for _ in range(N)])
sum_norm = 0
dict_norm = {}
for a in itertools.permutations(list(range(N))):
    for i in range(len(a) - 1):
        vector = tuple(xy[a[i + 1]] - xy[a[i]])
        if not vector in dict_norm:
            dict_norm[vector] = np.linalg.norm(vector)
        sum_norm += dict_norm[vector]
print((sum_norm / math.factorial(N)))

-        vector = xy[a[i + 1]] - xy[a[i]] -        if not tuple(vector) in dict_norm: -            dict_norm[tuple(vector)] = np.linalg.norm(vector) -        sum_norm += dict_norm[tuple(vector)] +        vector = tuple(xy[a[i + 1]] - xy[a[i]]) +        if not vector in dict_norm: +            dict_norm[vector] = np.linalg.norm(vector) +        sum_norm += dict_norm[vector]