Posterior Odds from Likelihood Ratio

Problem

In odds form, Bayes' rule is posterior odds = prior odds * likelihood ratio.

Given the prior odds and the likelihood ratio, return the posterior odds.

Hint

The likelihood ratio is evidence strength.

case 1

in: [1,4]

expected: 4

case 2

in: [0.25,10]

expected: 2.5

case 3

in: [3,0.5]

expected: 1.5

Starter codePython

def posterior_odds_from_likelihood_ratio(prior_odds, likelihood_ratio):
    # Your code here
    pass

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