mtcars Dataset

'data.frame':   32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

Call:
lm(formula = mpg ~ cyl + wt + cyl * wt, data = mtcars)

Residuals:
    Min      1Q  Median      3Q     Max 
-4.1513 -1.3798 -0.6389  1.4938  5.2523 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)   39.571      3.194  12.389 2.06e-12 ***
cyl6         -11.162      9.355  -1.193 0.243584    
cyl8         -15.703      4.839  -3.245 0.003223 ** 
wt            -5.647      1.359  -4.154 0.000313 ***
cyl6:wt        2.867      3.117   0.920 0.366199    
cyl8:wt        3.455      1.627   2.123 0.043440 *  
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 2.449 on 26 degrees of freedom
Multiple R-squared:  0.8616,    Adjusted R-squared:  0.8349 
F-statistic: 32.36 on 5 and 26 DF,  p-value: 2.258e-10