How can the Durbin-Watson statistic be best interpreted?A test for heteroscedasticityA measure of model fitA test for the normality of residualsA test for the presence of autocorrelation in the residuals
Question
How can the Durbin-Watson statistic be best interpreted?A test for heteroscedasticityA measure of model fitA test for the normality of residualsA test for the presence of autocorrelation in the residuals
Solution
The Durbin-Watson statistic is best interpreted as a test for the presence of autocorrelation in the residuals.
Here's a step-by-step interpretation:
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The Durbin-Watson statistic ranges from 0 to 4.
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A value of 2.0 means there is no autocorrelation detected in the sample.
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Values from 0 to less than 2 indicate positive autocorrelation, and values from 2 to 4 indicate negative autocorrelation.
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If the Durbin-Watson statistic is substantially less than 2, there is evidence of positive serial correlation.
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If the Durbin-Watson statistic is substantially more than 2, there is evidence of negative serial correlation.
So, it's not a test for heteroscedasticity, a measure of model fit, or a test for the normality of residuals. It's specifically used to detect autocorrelation in the residuals of a regression analysis.
Similar Questions
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