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Covers Markov processes, transition densities, and distribution conditional on information, discussing classification of states and stationary distributions.
Explores communicating classes in Markov chains, distinguishing between transient and recurrent classes, and delves into the properties of these classes.
Introduces simple linear regression, properties of residuals, variance decomposition, and the coefficient of determination in the context of Okun's law.