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RE: st: Very high t- statistics and very small standard errors
From
"Feiveson, Alan H. (JSC-SK311)" <[email protected]>
To
"[email protected]" <[email protected]>
Subject
RE: st: Very high t- statistics and very small standard errors
Date
Tue, 1 May 2012 08:08:30 -0500
Laurie - Another thing to consider is whether the 4 million observations are really independent. For example if you have 1,000,000 repeated observations on 4 subjects - that's still only 4 subjects - in which case you should not be running OLS.
Al
-----Original Message-----
From: [email protected] [mailto:[email protected]] On Behalf Of Laurie Molina
Sent: Monday, April 30, 2012 8:18 PM
To: [email protected]
Subject: Re: st: Very high t- statistics and very small standard errors
It is not the first time I hear people say that when you have a lot of
observations everything is significant... Is it because the lenght of
the confidence intervals is inversely related to the number of
observations considered? Or could you tell me what is the logic behind
saying that with a lot of observations everything is statistically
significant?
Thank you very much again!
On Mon, Apr 30, 2012 at 9:10 PM, Richard Williams
<[email protected]> wrote:
> At 07:54 PM 4/30/2012, Laurie Molina wrote:
>>
>> Hi everybody,
>> I'm running some OLS with around 4 million observations and 6
>> explanatory variables. My coefficients are always significants, with
>> very high t statistics and very low standard errors. for example t
>> statistic=20.6 and standard error= .000023. This is a cross sectional
>> data set.
>> I have run the VIF test and for all the variables the variance
>> inflation factor is less than 3.
>> I have also ran the Durbin test creating an index variable (_n) to see
>> wheter there is some sort of correlation in the error terms of my
>> regresion, but there is not.
>> Should I bee concerned about the significance of my coefficients? Is
>> there any problem with getting such a large t statistics and small
>> standard errors?
>> Thank you all in advance and best regards!!
>
>
> With 4 million cases it is hard not to get statistically significant
> results. Whether they are worth caring about is another matter. For example,
> a $2 difference in the incomes of men and women may be statistically
> significant. $2 is not the same as $0. But how much you should care is
> another matter. So, if everything is highly significant, I would ask myself
> what the substantive significance of the findings is. (Actually I would do
> that even if the results were not so significant - I think many people do
> not pay enough attention to "So What?" sorts of questions.)
>
>
> -------------------------------------------
> Richard Williams, Notre Dame Dept of Sociology
> OFFICE: (574)631-6668, (574)631-6463
> HOME: (574)289-5227
> EMAIL: [email protected]
> WWW: http://www.nd.edu/~rwilliam
>
>
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