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  • https://eng.libretexts.org/Bookshelves/Electrical_Engineering/Signal_Processing_and_Modeling/Discrete_Stochastic_Processes_(Gallager)/03%3A_Finite-State_Markov_Chains/3.01%3A_Introduction_to_Finite-state_Markov_Chains
    1 On the other hand, we frequently find situations where a small set of rv’s, say \(W, X, Y, Z\) satisfy the Markov condition that \(\operatorname{Pr}\{Z \mid Y, X, W\}=\operatorname{Pr}\{Z \mid Y\}\)...1 On the other hand, we frequently find situations where a small set of rv’s, say \(W, X, Y, Z\) satisfy the Markov condition that \(\operatorname{Pr}\{Z \mid Y, X, W\}=\operatorname{Pr}\{Z \mid Y\}\) and \(\operatorname{Pr}\{Y \mid X, W\}=\operatorname{Pr}\{Y \mid X\}\) but where the conditional distributions \(\operatorname{Pr}\{Z \mid Y\}\) and \(\operatorname{Pr}\{Y \mid X\}\) are unrelated.

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