# What does the Durbin Watson statistic tell us?

The Durbin Watson (DW) statistic is a test for autocorrelation in the residuals from a statistical regression analysis. The Durbin-Watson statistic will always have a value between 0 and 4. Values from 0 to less than 2 indicate positive autocorrelation and values from from 2 to 4 indicate negative autocorrelation.Click to see full answer. Also, how do you interpret the results of the Durbin Watson statistic?Computing and interpreting the Durbin–Watson statistic. is the sample autocorrelation of the residuals, d = 2 indicates no autocorrelation. The value of d always lies between 0 and 4. If the Durbin–Watson statistic is substantially less than 2, there is evidence of positive serial correlation.Also, why do we test for autocorrelation? The existence of autocorrelation in the residuals of a model is a sign that the model may be unsound. Autocorrelation is diagnosed using a correlogram (ACF plot) and can be tested using the Durbin-Watson test. This means that the data is correlated with itself (i.e., we have autocorrelation/serial correlation). One may also ask, what does a low Durbin Watson mean? If it is Durbin-Watson test statistic then it means the auto correlation is very low. A value of 2 means that there is no autocorrelation in the sample. Values approaching 0 indicate positive autocorrelation and values toward 4 indicate negative autocorrelation.What is the null hypothesis for Durbin Watson test?The Durbin-Watson test statistic tests the null hypothesis that the residuals from an ordinary least-squares regression are not autocorrelated against the alternative that the residuals follow an AR1 process. The Durbin-Watson statistic ranges in value from 0 to 4.