in this section you are asked to analyse the worst- case computational time complexity of python functions. Always identify the order of growth in the tightest and simplest possiple form using big-o notation, e.g, write O(n) instead of O(2n+n/2).

a) state the overall wrost-case time complexity of the below function and provide a short explaination of your answer. the function accepts as input a list, lst, of positive numbers. analyse the function in terms of the lengeth of the input list (n=len(lst))

def mystery(lst):

total = 0

n = len(lst)

for i in range(n):

for j in [i+1, n]:

total += sum(lst[i:j])

return total