\begin{Schunk}
\begin{Sinput}
 m0 <- lm(y ~ x1 * x2, data = dat) 
 summary(m0)
\end{Sinput}
\begin{Soutput}
Call:
lm(formula = y ~ x1 * x2, data = dat)

Residuals:
     Min       1Q   Median       3Q      Max 
-2.45205 -0.51588  0.05467  0.48869  2.37923 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept) -0.15901    0.11402  -1.395   0.1675    
x1           0.19033    0.10050   1.894   0.0623 .  
x2          -0.69192    0.09837  -7.034 1.02e-09 ***
x1:x2       -0.50231    0.08698  -5.775 1.88e-07 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 0.9864 on 71 degrees of freedom
Multiple R-squared:  0.5199,	Adjusted R-squared:  0.4996 
F-statistic: 25.63 on 3 and 71 DF,  p-value: 2.411e-11
\end{Soutput}
\end{Schunk}
