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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