\begin{Schunk}
\begin{Sinput}
 m2 <- lm(ynoe ~ x, data = dtest)
 summary(m2)
\end{Sinput}
\begin{Soutput}
Call:
lm(formula = ynoe ~ x, data = dtest)

Residuals:
       Min         1Q     Median         3Q        Max 
-7.193e-15 -2.259e-15 -1.152e-15  9.000e-18  1.293e-13 

Coefficients:
             Estimate Std. Error   t value Pr(>|t|)    
(Intercept) 3.000e+01  1.326e-15 2.262e+16   <2e-16 ***
x           2.000e+00  2.453e-16 8.154e+15   <2e-16 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.326e-14 on 98 degrees of freedom
Multiple R-squared:      1,	Adjusted R-squared:      1 
F-statistic: 6.648e+31 on 1 and 98 DF,  p-value: < 2.2e-16
\end{Soutput}
\begin{Sinput}
 ## Generates a warning
 ## Warning message: In summary.lm(m2) : essentially perfect fit: summary may be ## unreliable
\end{Sinput}
\end{Schunk}
