 This theorem is often useful for calculating credences that result from conditionalization on evidence \(E\), which are represented on the left side of the formula. Indeed, this theorem is very useful and important in statistical applications of Bayesian epistemology (see  section 3.5  below). For more on the significance of this theorem, see the entry on  Bayes’ theorem.  But this theorem is not essential to some other applications of Bayesian epistemology. Indeed, the case studies in the tutorial section make no reference to Bayes’ theorem. As Earman (1992: ch. 1) points out in his presentation of Bayes’ (1763) seminal essay, Bayesian epistemology is Bayesian not really because Bayes’ theorem is used in a certain way, but because Bayes’ essay already contains the core ideas of Bayesian epistemology: Probabilism and the Principle of Conditionalization.