\begin{Schunk}
\begin{Sinput}
 modpoly3 <- lm(y~ poly(x,2), data = dat)
 summary(modpoly3)
\end{Sinput}
\begin{Soutput}
Call:
lm(formula = y ~ poly(x, 2), data = dat)

Residuals:
     Min       1Q   Median       3Q      Max 
-1086.06  -258.65    -0.37   280.29  1314.22 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  -259.97      19.76 -13.157   <2e-16 ***
poly(x, 2)1 -4331.39     395.18 -10.961   <2e-16 ***
poly(x, 2)2  -880.94     395.18  -2.229   0.0264 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 395.2 on 397 degrees of freedom
Multiple R-squared:  0.2396,	Adjusted R-squared:  0.2358 
F-statistic: 62.55 on 2 and 397 DF,  p-value: < 2.2e-16
\end{Soutput}
\end{Schunk}
