Consider flipping a biased coin where p(z = H | θ1) = θ1. However, we cannot directly observe the result z. Instead, someone reports the result to us, which we denotey by x. Further, there is a chance that the result is reported incorrectly if it’s a head. Specifically, we have p(x = H | z = H, θ2) = θ2 and p(x = T | z = T) = 1. 1. Show that p(x = H | θ1, θ2) = θ1θ2. 2. Given a set of reported results Dr of size Nr, where the number of heads is nh and the number of tails is nt. Can we estimate θ1 and θ2 using MLE? Explain your judgment.