Using Bayes' Rule to Update an Event's Probabilities Based on the Outcomes of Partially Similar Events

There is a widely known Bayesian solution to the problem of updating the probability of an event occurring given information on the outcome of n completely similar events. But in many, if not most, cases, we only have information on partially similar events. For example, firms must assess the probability of a new product being successful given information on past products that are only partially similar to the new product. This paper shows how the well‐known Bayesian solution for completely similar events can be extended to solve the problem with partially similar past events.