> ##  Girder Exp't
> data<-read.table("http://www2.isye.gatech.edu/%7Ejeffwu/book/data/girder.dat", h=T)
> data
  Aarau Karlsruhe Lehigh Cardiff
1 0.772     1.186  1.061   1.025
2 0.744     1.151  0.992   0.905
3 0.767     1.322  1.063   0.930
4 0.745     1.339  1.062   0.899
5 0.725     1.200  1.065   0.871
6 0.844     1.402  1.178   1.004
7 0.831     1.365  1.037   0.853
8 0.867     1.537  1.086   0.858
9 0.859     1.559  1.052   0.805
> y<-c(t(data))  # row-wise
> y
 [1] 0.772 1.186 1.061 1.025 0.744 1.151 0.992 0.905 0.767 1.322 1.063 0.930
[13] 0.745 1.339 1.062 0.899 0.725 1.200 1.065 0.871 0.844 1.402 1.178 1.004
[25] 0.831 1.365 1.037 0.853 0.867 1.537 1.086 0.858 0.859 1.559 1.052 0.805
> girder <- rep(1:9, rep(4,9))
> girder
 [1] 1 1 1 1 2 2 2 2 3 3 3 3 4 4 4 4 5 5 5 5 6 6 6 6 7 7 7 7 8 8 8 8 9 9 9 9
> method<-rep(1:4, 9)
> method
 [1] 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4
> 
> g<-lm(y~as.factor(girder)+as.factor(method))
> anova(g)    
Analysis of Variance Table

Response: y
                  Df  Sum Sq Mean Sq F value    Pr(>F)    
as.factor(girder)  8 0.08949 0.01119  1.6189    0.1717    
as.factor(method)  3 1.51381 0.50460 73.0267 3.296e-12 ***
Residuals         24 0.16584 0.00691                      
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 
> 
> # the first 3 t values (i.e. t statistics for A vs K, A vs L, A vs C) can be read from the summary (because the default contrast coding is baseline constraint)
> summary(g)

Call:
lm(formula = y ~ as.factor(girder) + as.factor(method))

Residuals:
     Min       1Q   Median       3Q      Max 
-0.14261 -0.03201  0.00668  0.02838  0.17683 

Coefficients:
                   Estimate Std. Error t value Pr(>|t|)    
(Intercept)         0.77919    0.04799  16.236 1.91e-14 ***
as.factor(girder)2 -0.06300    0.05878  -1.072  0.29446    
as.factor(girder)3  0.00950    0.05878   0.162  0.87296    
as.factor(girder)4  0.00025    0.05878   0.004  0.99664    
as.factor(girder)5 -0.04575    0.05878  -0.778  0.44397    
as.factor(girder)6  0.09600    0.05878   1.633  0.11547    
as.factor(girder)7  0.01050    0.05878   0.179  0.85972    
as.factor(girder)8  0.07600    0.05878   1.293  0.20832    
as.factor(girder)9  0.05775    0.05878   0.983  0.33565    
as.factor(method)2  0.54522    0.03919  13.914 5.51e-13 ***
as.factor(method)3  0.27133    0.03919   6.924 3.68e-07 ***
as.factor(method)4  0.11067    0.03919   2.824  0.00939 ** 
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.' 0.1 ` ' 1 

Residual standard error: 0.08313 on 24 degrees of freedom
Multiple R-Squared: 0.9063,	Adjusted R-squared: 0.8633 
F-statistic: 21.09 on 11 and 24 DF,  p-value: 1.047e-09