You have a coin that may or may not be biased. Either the coin is unbiased making it equally likely that you will get heads or tails. Or it is biased towards landing on heads (let us say 70% of the time). Or it is biased similarly towards landing on tails. You assume that either of these scenarios are equally likely. You toss the coin 15 times and dotice that you got 10 heads. How do your assumptions change? Give the Bayesian estimate of the probability of the coin landing on heads (along with its posterior risk).