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Question: Consider the query P(Rain(Sprink1er = true, WetGrass = true) in Figure (a) and how MCMC can answer it.

a. How many states does the Markov chain have?

b. Calculate the transition matrix Q containing q(y + y') for all y, y'.

c. What does Q~, the square of the transition matrix, represent?

d. What about Qn as n -t GO?

e. Explain how to do probabilistic inference in Bayesian networks, assuming that Qn is available. Is this a practical way to do inference?

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