Some ARIMA models do not require a constant term. What determines the need for it? (Points : 3.5)

The t-value of the coefficients.

The LBQ values.

The mean value of the residuals.

The mean or intercept value of the last differenced data series.

A second order MA model implies that (Points : 3.5)

the autocorrelation function of the data has two significant early lags. there are two coefficients in the ARIMA model excluding the constant term. the partial autocorrelation function of the data has two significant lags. 1. and 2. above

Which ARIMA model type is used to derive forecasts of a variable based only on a linear function of its past data values? (Points : 3.5)

a moving average model onlya second order moving average model an ARMA model an autoregressive model Any exponential smoothing model

The "I" in the ARIMA technique represents (Points : 3.5)

the minimum error that is generated by the Moving Average process the individual correlations for each lag period differencing to create a stationary data series autoregressiveness of the appropriate model