The classical view sketched above entails a violation of this: the impact of the observed data may be different depending on the probability of other samples than the observed one, because those other samples come into play when determining regions of acceptance and rejection. The Bayesian procedures discussed in   Section 4, on the other hand, uphold the likelihood principle: in determining the posterior distribution over hypotheses only the prior and the likelihood of the observed data matter. In the debate over optional stopping and in many of the other debates between classical and Bayesian statistics, the likelihood principle is the focal point.