2: Bayesian Updating A potential buyer is trying to decide if a new motorcycle is good or bad. The prior belief that the motorcycle is good is 50%. Then the potential buyer receives signals (test rides), where g represents a good test ride performance and b represents a bad test ride performance by the motorcycle. Also good motorcycles perform well on test rides with 70% probability and bad motorcycles ride poorly on test rides with the same 70% probability. Given that the potential buyer goes on a three good test rides, what is her posterior probability assessment that the motorcycle is a good one