Jackknife估计

def solve():
    import numpy as np
    data = [____,____,____,____,____]
    n = len(____)
    full_mean = np.mean(____)
    jackknife_means = []
    for i in range(____):
        sample = data[:i] + data[i+____:]
        jackknife_means.append(np.mean(____))
    bias = (____) * (np.mean(____) - full_mean)
    print(____)