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 Durbinâ€“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 Durbinâ€“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.