Statistics undergraduates were given two different coinsA and B. each with different odds of showing heads. ,9); and p3, respectively. The students were tasked with exploring the topic of sample distributions as follows: For a total of N sets, pick one of the coins with probabilityr m versus 1:3 2 1 11A. and toss it 10 times in a row, recording the observed number of heads [each of these observed numbers is a sample of a binomial distribution, and the observed head counts for each coin represent a distribution of sample statistics that should inform about the underlying odds pd and p3}. Unfortunately, only after repeating this torN = 100 sets [so a total of 1.000 tosses) did the students realize that they forgot to record which coin they had picked for each set... Since they started work on their project way too late. there is no time left to simply repeat the experiments. Here. we want to use EM to help them not fail the class. after all. ta} Identify the observed and latent variables. {b} Identify all parameters that we need to learn. to} Describe the E-step (as you would explain it to a non-math scientist}? {d} Describe the lull-step [as 1you Iwould explain it to a non-math scientist]? {e} What do we know about convergence of such an EM approach? What can we do about it