Novelty Effect

Problem

Estimate the novelty effect as the change in lift from the first k days to the remaining days: mean(lifts[k:]) - mean(lifts[:k]).

Return 0.0 if k is not within (0, len(lifts)).

Hint

A large drop after the first days suggests the early lift was a novelty spike.

case 1

in: [[5,4,2,1],1]

expected: -2.6666666666666665

case 2

in: [[1,2,3,4],2]

expected: 2

case 3

in: [[3],1]

expected: 0

case 4

in: [[],1]

expected: 0

Starter codePython

def novelty_effect(lifts, k):
    # Your code here
    pass

4 test cases · run your code against them in the editor