Application5

Below is the summary of the simulation performed on 5 samples (each containing 4 numbers) and the subroutines used to compute the mean values.

def kahansum(input):

    summ = c = 0

    for num in input:

        y = num - c

        t = summ + y

        c = (t - summ) - y

        summ = t

    return summ

def neumaiersum(input):

    sum = input[0]

    c = 0.0

    for i in range(1, len(input)):

        t = sum + input[i]

        if abs(sum) > abs(input[i]):

            c += (sum - t) + input[i]

        else:

            c += (input[i] - t) + sum

        sum = t

    return sum + c

def knuth_mean(input):

    mean = 0

    m = 1

    for n in input:

        d = n - mean

        tot = m

        mean += d / tot

        m += 1

    return mean