A larger sample size increases the power of a hypothesis test, which is the probability of correctly rejecting a false null hypothesis. Power is important because it reduces the likelihood of a Type II error (failing to detect a true effect), ensuring the test is sensitive enough to identify meaningful differences or relationships.