A likelihood ratio expresses how relatively more likely an observation is, comparing one hypothesis to another. For example, if we're investigating the murder of Mr. Boddy and the suspects are Colonel Mustard and Miss Scarlet, and Mr. Boddy was poisoned, we might think that Miss Scarlet is twice as likely to use poison as Colonel Mustard - a likelihood ratio of 2:1. This could be true if their respective probabilities of using poison were 20% versus 10%, or if the probabilities 4% versus 2%. What matters is the ratio, not the absolute magnitudes. This ratio summarizes the strength of the evidence represented by the observation that Mr. Boddy was poisoned - under Bayes's Rule, the evidence points to Miss Scarlet to the same degree whether the absolute probabilities are 20% vs. 10%, or 4% vs. 2%