Dear R-group,
We have begun to use it for teaching Statistics. In this context we have run
into a problem with linear regression
where we found the results of are confusing.
Specifically, considering the data:
x=c(4,5,6,3,7,8,10,14,13,15,6,7,8,10,11,4,5,17,12,11)
y=c(rep(7,20))
and settings
regress=lm(y~x)
summary(regress) gives the following results:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 7.000e+00 8.623e-17 8.118e+16 <2e-16 ***
x -1.116e-17 8.956e-18 -1.247e+00 0.229
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Residual standard error: 1.565e-16 on 18 degrees of freedom
Multiple R-squared: 0.6416, Adjusted R-squared: 0.6217
Other statistical packages respond that the analysis can not be done. We think
that the results of R-squared
does not seem to express the variability of y explained by x. We would greatly
appreciate any clarification you
could provide.
Thanks you and best regards.
Marta di Nicola e Colagrande Vittorio
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