Lab 10: Bayesian Statistics In order to understand how Bayesian statistics works, we're going to start with a simple scenario. Imagine you are studying coastal birds of southern California. Two models describing the abundance of seagulls and cormorants have been proposed. Model 1 predicts that you will observe 75% cormorants and 25% seagulls, while model 2 predicts that each species will make up 50% of your observations. Heading out to Ballona Creek to observe birds, you want to know the probability that model 1 is true. Let's call "model 1 being true" event A and "observing a bird (either seagull or cormorant)" event B. We can easily find ( ) p(BA), but using this information to determine the probability that model 1 is correct requires an equation known as Bayes' theorem. ( ) = ( ) ( ) ( ) p(AB)= p(B) p(BA)p(A)