 Solution

For $\mathbb{P}(B)>0$, the conditional probability is $\mathbb{P}(A\mid B)=\mathbb{P}(A\cap B)/\mathbb{P}(B)$. Since the events $B_i$ partition the sample space, their intersections with $A$ are disjoint and exhaust $A$. The law of total probability therefore gives $\mathbb{P}(A)={\sum }_j\mathbb{P}(A\mid B_j)\mathbb{P}(B_j)$. Substituting this and $\mathbb{P}(A\cap B_i)=\mathbb{P}(A\mid B_i)\mathbb{P}(B_i)$ into the definition proves Bayes' theorem:The denominator is positive by the given hypothesis on $A$.