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Suppose a process can be considered to be in one of two states (let's call them state A and state B), but the next state of the process depends not only on the current state but also on the previous state as well. We can still describe this process using a Markov chain, but we will now need four states. The chain will be in state (X Y) , if the process is currently in state and was previously in state .
(a) Show that the transition probability matrix of such a four-state Markov chain must have zeros in at least half of its entries.
(b) Suppose that the transition probability matrix is given by
Find the steady-state distribution of the Markov chain.
(c) What is the steady-state probability that the underlying process is in state A?
a genetic experiment involving peas yielded one sample of offspring consisting of 414 green peas and 153 yellow peas.
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Calculate the 95% confidence maximum error of estimate for a binomial experiment of 1027 trials that result in an observed proportion of .47.
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