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.