# Question

1. A forecast is the prediction of a future value of a time series.

2. The approximate prediction interval ŷ ± 2se works well for forecasts from a polynomial trend model particularly when extrapolating away from the observations.

3. A moving average smoothes a time series Yt by averaging Yt with nearby observations before and after time period t.

4. The seasonal component of a time series consists of a regular, periodic pattern.

5. Outliers produce jumps in the exponential smooth of a time series.

6. With enough powers, a polynomial trend obtains a large value of R2 for any time series.

2. The approximate prediction interval ŷ ± 2se works well for forecasts from a polynomial trend model particularly when extrapolating away from the observations.

3. A moving average smoothes a time series Yt by averaging Yt with nearby observations before and after time period t.

4. The seasonal component of a time series consists of a regular, periodic pattern.

5. Outliers produce jumps in the exponential smooth of a time series.

6. With enough powers, a polynomial trend obtains a large value of R2 for any time series.

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