Radford Neal:
>> Coefficients:
>> Estimate Std. Error t value Pr(>|t|)
>> (Intercept) 15.51024 0.62466 24.83 <2e-16 ***
>> x 0.40863 0.01898 21.52 <2e-16 ***
>> ---
>> Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
>>
Vadim and Oxana Marmer:
>it speaks for itself: how often do you see t-stat=22? Actually, I would
>recommend you to repeat this experiment for example 100 times and to check
>how many time you cannot reject b=0.
Radford Neal:
>> adjusting for autocorrelation you will conclude that you effectively
>> have about five data points' worth of information. I don't think you
>> will reject the null hypothesis.
Vadim and Oxana Marmer:
>the only adjustment that is going to work here is to difference the data.
If you had actually read the lines you quote from my post, and the
preceding numerical output, you would have discovered that looking at
the autocovariance estimates for the residuals of the regression DOES
reveal very large autocorrelations, which WILL lead you to conclude
that the small p-values found by assuming independent residuals are
not valid. I don't see why you are trying to deny this obvious fact.
Radford Neal
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