> tl.mod1 <- aov(tool_life ~ x1 + x2 + I(x1^2) + I(x2^2) + I(x1*x2) + trt)
> anova(tl.mod1)
Analysis of Variance Table

Response: tool_life
           Df Sum Sq Mean Sq  F value    Pr(>F)    
x1          1  364.1   364.1   7.0020 0.0456386 *  
x2          1 5568.6  5568.6 107.0886 0.0001450 ***
I(x1^2)     1  630.3   630.3  12.1218 0.0176278 *  
I(x2^2)     1 3453.3  3453.3  66.4105 0.0004519 ***
I(x1 * x2)  1  930.2   930.2  17.8894 0.0082515 ** 
trt         3  110.8    36.9   0.7102 0.5862842    
Residuals   5  260.0    52.0                       
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 
> 
> tl.mod2 <- aov(tool_life ~ x1 + x2 + I(x1^2) + I(x2^2) + I(x1*x2))
> summary.lm(tl.mod2) 

Call:
aov(formula = tool_life ~ x1 + x2 + I(x1^2) + I(x2^2) + I(x1 * 
    x2))

Residuals:
     Min       1Q   Median       3Q      Max 
-13.0000  -1.6977   0.4435   2.8442   7.0000 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  169.000      2.779  60.806 5.95e-12 ***
x1             6.746      2.407   2.803  0.02310 *  
x2            26.383      2.407  10.961 4.26e-06 ***
I(x1^2)      -10.875      2.505  -4.341  0.00248 ** 
I(x2^2)      -21.625      2.505  -8.632 2.52e-05 ***
I(x1 * x2)   -15.250      3.404  -4.480  0.00206 ** 
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 

Residual standard error: 6.808 on 8 degrees of freedom
Multiple R-squared: 0.9672,     Adjusted R-squared: 0.9468 
F-statistic: 47.24 on 5 and 8 DF,  p-value: 9.99e-06 

>