import numpy as np

N=int(eval(input()))



str_list = input().split(' ')

A = [int(x) for x in str_list]

A = np.array(A)



while len(A)>1:

    first_min = A[A.argmin()]

    #print(first_min)

    A = np.delete(A, A.argmin())

    second_min = A[A.argmin()]

    #print(second_min)

    A = np.delete(A, A.argmin())

    mean = (first_min+second_min)/2.0

    A = np.append(A, mean)

    #print(A)

print(mean)

N=int(eval(input()))

str_list = input().split(' ')

v = [int(x) for x in str_list]



while len(v)>1:

    v.sort(reverse=True)

    val1 = v.pop()

    val2 = v.pop()

    mean = (val1 + val2) / 2.0

    v.append(mean)

print((v[0]))

import numpy as np

N = int(eval(input()))
str_list = input().split(" ")
A = [int(x) for x in str_list]
A = np.array(A)
while len(A) > 1:
    first_min = A[A.argmin()]
    # print(first_min)
    A = np.delete(A, A.argmin())
    second_min = A[A.argmin()]
    # print(second_min)
    A = np.delete(A, A.argmin())
    mean = (first_min + second_min) / 2.0
    A = np.append(A, mean)
    # print(A)
print(mean)

N = int(eval(input()))
str_list = input().split(" ")
v = [int(x) for x in str_list]
while len(v) > 1:
    v.sort(reverse=True)
    val1 = v.pop()
    val2 = v.pop()
    mean = (val1 + val2) / 2.0
    v.append(mean)
print((v[0]))

-import numpy as np - -A = [int(x) for x in str_list] -A = np.array(A) -while len(A) > 1: -    first_min = A[A.argmin()] -    # print(first_min) -    A = np.delete(A, A.argmin()) -    second_min = A[A.argmin()] -    # print(second_min) -    A = np.delete(A, A.argmin()) -    mean = (first_min + second_min) / 2.0 -    A = np.append(A, mean) -    # print(A) -print(mean) +v = [int(x) for x in str_list] +while len(v) > 1: +    v.sort(reverse=True) +    val1 = v.pop() +    val2 = v.pop() +    mean = (val1 + val2) / 2.0 +    v.append(mean) +print((v[0]))