 The problem with the paradoxes of relevance is that in complex situations there is no single likelihood ratio that corresponds to a piece of evidence. The problematic cases focus on a single likelihood ratio based on non-exclusive or non-exhaustive hypotheses. However, evidence can be relevant so long as it has a probabilistic impact on a pertinent sub-hypothesis, even without having a probabilistic impact on the prosecutor’s or defense’s ultimate hypotheses. When this happens, the evidence is relevant, in agreement with Rule 401 of the Federal Rules of Evidence. Bayesian networks (discussed in the preceding section) help to see how pieces of evidence can increase or decrease the probability of different sub-hypotheses (for more details, see de Zoete et al. 2019).