ARIMA Models Quiz

Answers and explanations appear as you take the quiz.

1. In ARIMA(p,d,q), what does p specify?
   • The number of autoregressive lags
   • The differencing count
   • The moving-average error lags
   • The seasonal period
2. In ARIMA(p,d,q), what does d count?
   • Lagged forecast errors
   • Nonseasonal differencing operations
   • Seasonal cycles per year
   • Number of exogenous regressors
3. What does q represent in the nonseasonal order?
   • Seasonal differencing
   • Lagged observed values
   • Lagged forecast-error terms
   • The forecast horizon
4. What does s=12 commonly represent in monthly seasonal ARIMA?
   • A twelve-month forecast horizon
   • Twelve ordinary AR lags
   • Twelve differences required
   • A seasonal period of twelve observations
5. What does the seasonal differencing order D do?
   • Adds D ordinary error lags
   • Differences observations separated by the seasonal period
   • Selects the number of forecast steps
   • Removes every trend and residual pattern
6. Why can excessive differencing be harmful?
   • It makes p and q equal
   • It always increases forecast accuracy
   • It can remove useful structure and add unnecessary noise
   • It converts seasonal periods into labels
7. What should be checked after fitting an ARIMA model?
   • Whether all future values are positive
   • Only whether training predictions are identical to observations
   • Whether the order contains equal p and q
   • Residual patterns and time-ordered forecast performance
8. Why compare an ARIMA forecast with a seasonal-naive baseline?
   • To determine whether model complexity adds useful forecast skill
   • To guarantee the ARIMA model is stationary
   • To calculate the number of seasonal periods
   • To replace residual diagnostics