import itertools



N = int(eval(input()))

points = [tuple(map(int, input().split())) for _ in range(N)]

sum_dist = 0



pattern = list(range(N))

patterns = list(itertools.permutations(pattern))



for pattern in patterns:

    tmp_dist = 0

    for i in range(N - 1):

        x, y = points[pattern[i]]

        nx, ny = points[pattern[i + 1]]

        tmp_dist += ((nx - x) ** 2 + (ny - y) ** 2) ** 0.5

    sum_dist += tmp_dist



print((sum_dist / len(patterns)))
N = int(eval(input()))

points = [list(map(int, input().split())) for _ in range(N)]

sum_dist = 0



for i in range(N):

    for j in range(i + 1):

        sum_dist += (

            (points[j][0] - points[i][0]) ** 2 + (points[j][1] - points[i][1]) ** 2

        ) ** 0.5

print((sum_dist * 2 / N))
import itertools

N = int(eval(input()))
points = [tuple(map(int, input().split())) for _ in range(N)]
sum_dist = 0
pattern = list(range(N))
patterns = list(itertools.permutations(pattern))
for pattern in patterns:
    tmp_dist = 0
    for i in range(N - 1):
        x, y = points[pattern[i]]
        nx, ny = points[pattern[i + 1]]
        tmp_dist += ((nx - x) ** 2 + (ny - y) ** 2) ** 0.5
    sum_dist += tmp_dist
print((sum_dist / len(patterns)))

N = int(eval(input()))
points = [list(map(int, input().split())) for _ in range(N)]
sum_dist = 0
for i in range(N):
    for j in range(i + 1):
        sum_dist += (
            (points[j][0] - points[i][0]) ** 2 + (points[j][1] - points[i][1]) ** 2
        ) ** 0.5
print((sum_dist * 2 / N))

-import itertools - -points = [tuple(map(int, input().split())) for _ in range(N)] +points = [list(map(int, input().split())) for _ in range(N)] -pattern = list(range(N)) -patterns = list(itertools.permutations(pattern)) -for pattern in patterns: -    tmp_dist = 0 -    for i in range(N - 1): -        x, y = points[pattern[i]] -        nx, ny = points[pattern[i + 1]] -        tmp_dist += ((nx - x) ** 2 + (ny - y) ** 2) ** 0.5 -    sum_dist += tmp_dist -print((sum_dist / len(patterns))) +for i in range(N): +    for j in range(i + 1): +        sum_dist += ( +            (points[j][0] - points[i][0]) ** 2 + (points[j][1] - points[i][1]) ** 2 +        ) ** 0.5 +print((sum_dist * 2 / N))