Firefighter 1 & 2 final UPDATED ACTUAL Exam Questions and CORRECT Answers

Firefighter 1 & 2 final UPDATED ACTUAL Exam Questions and CORRECT Answers

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A white noise process has zero auto-covariance for all lags including lag zero. - (answer)False



If a time series is Gaussian then it is non-stationary. - (answer)False



AR(p) processes are always invertible. - (answer)True



The ACF plot can always be used to determine the order q of ARMA(p,q) models. - (answer)False



In some cases, the PACF plot can be used to determine the order p of ARMA(p,q) models. - (answer)True



The PACF of an ARMA(p,q) process cuts off after lag p. - (answer)False. (The PACF of an ARMA(p,q)
process tails off, while the PACF of an AR(p) process cuts off after lag p.)



MA(q) processes are always causal. - (answer)True



If Xt and Ytϕ1 are independent AR(1) processes, then Xt+Yt ϕ1 is an AR(2) process. - (answer)False. (The
order of the sum of two independent AR processes is not necessarily the sum of each individual
processes' order.)



Let Wt be a white noise process. Then Xt=Wt−Wt−1 is stationary. - (answer)True



An ARIMA(p,0,q) model is always stationary. - (answer)False



There is no auto-correlation in an ARIMA(1,d,q) process. - (answer)False