Durbin-Watson+Autocorrelation+Test

Durbin-Watson Autocorrelation Test (Regression) (GWU EMSE-271)
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"The **Durbin–Watson statistic** is a test statistic used to detect the presence of autocorrelation in the residuals from a regression analysis.

"Since //d// is approximately equal to 2(1-//r//), where //r// 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. As a rough rule of thumb, if Durbin–Watson is less than 1.0, there may be cause for alarm. Small values of //d// indicate successive error terms are, on average, close in value to one another, or positively correlated. If //d// > 2 successive error terms are, on average, much different in value to one another, i.e., negatively correlated. In regressions, this can imply an underestimation of the level of statistical significance." - [|Wikipedia]


 * Sources:**
 * Durbin–Watson statistic. (2009, October 27). In //Wikipedia, The Free Encyclopedia//. Retrieved 21:09, December 7, 2009, from []
 * Analyzing Multivariate Data, by James Lattin, Douglas Carroll and Green ([|Amazon]), pp. 61-62
 * EMSE 271, Fall 2009