Autocorrelation Lag-1

Problem

Return the lag-1 autocorrelation of data: sum((x_i - mean)*(x_(i-1) - mean)) / sum((x_i - mean)^2) for i from 1 to n-1. Return 0.0 when n < 2 or all values are equal.

Hint

The denominator is the total sum of squares; the numerator only uses adjacent pairs.

Test cases

case 1

in: [[1,2,3,4,5]]

expected: 0.4

case 2

in: [[1,-1,1,-1,1]]

expected: -0.7999999999999998

case 3

in: [[3,3]]

expected: 0

case 4

in: [[1,2]]

expected: -0.5

case 5

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

expected: 0.057142857142857106

Starter codePython

def autocorrelation_lag1(data):
    # Your code here
    pass

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