1. Which ARIMA model type is used to derive forecasts of a variable based only o

Question

1. Which ARIMA model type is used to derive forecasts of a variable based only on a linear function of its lagged data values?

a)

b)

c)

d)

an autoregressive model

2. Autocorrelations differ from partial autocorrelations in that

a)

b)

c)

d)

e)

a)

a moving average model

b)

a second order moving average model

c)

an ARMA model

d)

an autoregressive model

2. Autocorrelations differ from partial autocorrelations in that

a)

autocorrelation is the total correlation effect between lag values of a time series that could include previous lag autoregressive effects while partial autocorrelation is the direct correlation only between the specific lag value and the data observation.

b)

in autocorrelation other lag effects are allowed to vary while in partial autocorrelation the other lagged effects are held constant.

c)

partial autocorrelation is the indirect correlation only between the specific lag value of the variable and the variable observation while autocorrelation is the direct effect be observations and the lagged observations.

d)

partial autocorrelation is closer to true correlation since the significance can be measured by t values while autocorrelation cannot.

e)

only a and b above.

Explanation / Answer

1. An autoregressive model type is used to derive forecasts of a variable based only on a linear function of its lagged data values. So the correct option is D.

2. Autocorrelations differ from partial autocorrelations in that partial autocorrelation is the indirect correlation only between the specific lag value of the variable and the variable observation while autocorrelation is the direct effect be observations and the lagged observations. So the correct option is C.

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