After a linear forecasting model is found for a time series, if the Durbin-Watson statistic is less than dL this means that:
A) no positive autocorrelation exists, the linear model is adequate.
B) positive autocorrelation exists, a nonlinear model should be tried.
C) no positive autocorrelation exists, a nonlinear model should be tried.
D) positive autocorrelation exists, the linear model is adequate.

Question

Quizplus · Accepted Answer

The Durbin-Watson statistic tests for the presence of autocorrelation in the residuals from a statistical regression analysis. If the Durbin-Watson statistic is less than the lower bound (dL), it suggests evidence of positive autocorrelation. This means the residuals are correlated with each other, which is a violation of the assumptions of the linear regression model, indicating that a different model, possibly nonlinear, might be more appropriate.

After a Linear Forecasting Model Is Found for a Time