Across
- 3. Any series of observations that can be arranged chronologically.
- 5. The variation in y that is explained by the regression equations.
- 7. Correlation between successive observations in a time series.
- 8. The letter that represents the standard error of the estimate - measures the variability of the actual Y values from the line of regression.
- 9. y(t)/y(t-1) versus t - A point on this graph indicates how much the current value of the series has increased or decreased relative to the previous value.
- 10. The mean of the k most recent observations.
- 11. The total variation of y in the sample.
- 12. This model assumes that the values of the time series are relatively unchanging from period to period. The current value of the series is used as the forecast for the next period.
- 13. This is where you have constant incremental change, that is, the expected first differences are the same for all t.
Down
- 1. A wavelike pattern about a long-term trend that is generally apparent over a number of years.
- 2. This is where the amount of change (but not the direction) varies as time changes.
- 3. A long term relatively smooth pattern or direction that the series exhibits. Its duration is typically more than a year.
- 4. Measures forecast accuracy by averaging the magnitudes of the forecast errors, that is, the absolute values of the residuals.
- 5. The estimate of the seasonal irregular component of the multiplicative model.
- 6. Test used to test for a significant seasonal effect.
- 10. Measures forecast accuracy by averaging the square of the magnitudes of the forecast errors.