[R] newbie's additional (probably to some extent OT) questions
JB
jblazi at gmx.de
Thu Nov 6 21:50:41 CET 2003
(1)
So finally, thank to your help I have this:
summary(lm(x ~ 0+I(t^2)))
And then I get this result:
=================================================
Call:
lm(formula = x ~ 0 + I(t^2))
Residuals:
Min 1Q Median 3Q Max
-3.332e-02 -9.362e-03 1.169e-05 1.411e-02 3.459e-02
Coefficients:
Estimate Std. Error t value Pr(>|t|)
I(t^2) 0.0393821 0.0001487 264.8 <2e-16 ***
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 0.01945 on 18 degrees of freedom
Multiple R-Squared: 0.9997, Adjusted R-squared: 0.9997
F-statistic: 7.014e+04 on 1 and 18 DF, p-value: < 2.2e-16
=================================================
I see in MuPad, that Delta^2 is 0.006813. Now is not the standard error the
square root of Delta^2? Should I not get 0.069 as standard error?
(2)
When I use the model
summary(lm(x ~ I(t^2)))
I get (of course) another result with a slightly smaller Delta^2. But I do
not expect such an error as this would mean that there was a systematic
error in our measurement of the distance and if I understand the result of
R correctly, the error was 0.04m which is impossible:
==========================================================
Call:
lm(formula = x ~ I(t^2))
Residuals:
Min 1Q Median 3Q Max
-0.0202520 -0.0116533 -0.0006036 0.0036699 0.0432987
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 0.0427606 0.0161085 2.655 0.0167 *
I(t^2) 0.0379989 0.0005367 70.801 <2e-16 ***
---
Signif. codes: 0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1
Residual standard error: 0.01683 on 17 degrees of freedom
Multiple R-Squared: 0.9966, Adjusted R-squared: 0.9964
F-statistic: 5013 on 1 and 17 DF, p-value: < 2.2e-16
=====================================================
What is going on here?
(Sorry but I am only a high school teacher and have not much idea of
statistics.)
TIA,
JB
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