this is what I mentioned today (durbin-watson)

[chou...@msu.edu]

 http://www.imm.bwl.uni-muenchen.de/dateien/3_lehre/market_analysis/durbin_watson_tables.pdf

[Doosoo Kim]

Oh thanks!

It makes a lot of sense :)

The relevent part is on the second page:

If the observed value of the test statistic is less than the tabulated lower bound, then you 

should reject the null hypothesis of non-autocorrelated errors in favor of the hypothesis 

of positive first-order autocorrelation. Since 0.24878 is less than 1.377, we reject the 

null hypothesis. If the test statistic value were greater than dU, we would not reject the 

null hypothesis.

For models with an intercept, if the observed test statistic value is greater than 2, 

then you want to test the null hypothesis against the alternative hypothesis of negative 

first-order autocorrelation. To do this, compute the quantity 4-d and compare this value 

with the tabulated values of dL and dU as if you were testing for positive 

autocorrelation

Best,

Doosoo

On 19 April 2013 22:10, <chou...@msu.edu> wrote:

 http://www.imm.bwl.uni-muenchen.de/dateien/3_lehre/market_analysis/durbin_watson_tables.pdf

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[riju joshi]

Thank you Annie and Doosoo. This was very helpful!
:-)