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Re: st: Very high t- statistics and very small standard errors

From   Nick Cox <>
Subject   Re: st: Very high t- statistics and very small standard errors
Date   Wed, 2 May 2012 14:34:43 +0100

If your data are not time series, it is hard to see that Durbin-Watson
tests make any sense. (It is also puzzling how you managed to
calculate them.)

Alan Feiveson's point was I think to wonder about any cluster or
clumping structure: for example, millions of people would often show
some similarities within families or communities.


On Wed, May 2, 2012 at 2:09 PM, Laurie Molina <> wrote:
> Thank you all.
> I will try adding more variables to the model, and think on the
> economic vs statistical significance of the results (I will look for
> the appropiate null hypothesis, as opossed to the default zero).
> Regarding the independe of the observations I ran Durbin Watson
> (although my data is non time series), and the error term do not seem
> to be correlated among observations.
> Regards and thanks again,
> LM
> On Tue, May 1, 2012 at 7:36 PM, David Hoaglin <> wrote:
>> Laurie,
>> It's unusual to see such a large number of observations and so few
>> explanatory variables.  Often, as the amount of data increases, the
>> complexity of the model grows.  Do those 4 million observations
>> actually have no structure other than that described by the 6
>> explanatory variables?
>> David Hoaglin
>> On Mon, Apr 30, 2012 at 8:54 PM, Laurie Molina <> wrote:
>>> Hi everybody,
>>> I'm running some OLS with around 4 million observations and 6
>>> explanatory variables.

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