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Hey guys, in this video Im going to do this time series problem. It essentially is giving you a list of different time series or stochastic processes and its asking you to determine which of them, if any, are stationary. This question comes from the Brockwell and Davis time series book, where they define stationarity as weak stationarity. Theres technically a definition of weak stationarity and also strict stationarity but for time series, usually we want to just meet the definition of weak stationarity. Weak stationarity is a less strict stationarity assumption and its based on two parts. Its based on essentially looking for stationarity in the first moment and the second moment of your stochastic process. This definition is also from the Brockwell and Davis book and it says that a time series is weakly stationary if the first moment does not depend on time t, in other words that the mean is constant for your time series and that the autocovariance function for t and t plus a lag