Which of the following is true for an autoregressive model?Answer choicesSelect only one optionREVISITIn an autoregressive model, the value from a time series is regressed on future values from that same time seriesIn an autoregressive model, the value from a time series is regressed on previous values from that same time seriesIn an autoregressive model, the value from a time series is regressed on previous values from a different time seriesIn an autoregressive model, the value from a time series is regressed on future values from a different time series

Which of the following are the important characteristics that determine the choice of the forecasting model?Answer choicesSelect only one optionREVISITPatterns in the dataVolume of the dataVelocity of the dataVariety of Data

Which of the following sets of characteristics would usually best describe an autoregressive process of order 3 (i.e., an AR(3))?Group of answer choicesA slowly decaying acf, and a pacf with 3 significant spikesA slowly decaying pacf and an acf with 3 significant spikesAn acf and a pacf with 3 significant spikesA slowly decaying acf and pacf

Which of the following represents the characteristics of a stationary time series?Answer choicesSelect only one optionREVISITA series with a constant mean over a given time intervalA series with a constant mean and variance over a given time intervalA series with a constant mean and fluctuating variance over a given time intervalA series with a varying mean and constant variance over a given time interval

Which of the following uses a weighted average of past time series values as the forecast?Group of answer choicesThe qualitative methodExponential smoothingCorrelation analysisThe causal model

Consider two time series, {𝑥𝑡}𝑡=1𝑇 and {𝑦𝑡}𝑡=1𝑇, one generated using AR(1) and the other using MA(1), as follows:𝑥𝑡=𝛼+𝛽𝑥𝑡−1+𝜀𝑡, and𝑦𝑡=𝜇+𝜀𝑡+𝜃𝜀𝑡−1.Suppose 𝛽=𝜃=0.5.Based on the provided information, we can claim that:Group of answer choicesNone of the presented answers are correct.The first order autocorrelation of the series following the presented AR model is larger than the first order autocorreation of the series following the presented MA model.The autocorrelation functions of the two models are identical for lags greater than one.The second order autocorrelation of the series following the presented AR model is equal to zeroThe two step-ahead forecast of the series following the presented AR model is equal to the unconditional mean of the series.