> #6.5 Hot chip Example
> x<-matrix(c(
+ 3,4,4,
+ 3,4,2,
+ 3,4,1,
+ 4,1,4,
+ 3,3,3,
+ 2,5,3,
+ 2,2,3,
+ 1,2,1,
+ 3,1,3,
+ 3,4,2,
+ 3,3,4,
+ 5,4,5,
+ 1,1,1,
+ 1,1,3,
+ 4,5,1,
+ 5,3,1,
+ 2,3,1,
+ 1,2,3,
+ 1,2,3,
+ 2,3,3,
+ 2,2,4,
+ 3,4,1,
+ 3,3,1,
+ 1,1,4,
+ 1,1,4,
+ 4,3,5,
+ 4,1,1,
+ 2,1,1,
+ 1,4,1,
+ 2,1,4,
+ 3,4,2,
+ 3,1,3,
+ 4,2,4,
+ 1,3,1,
+ 2,3,2,
+ 1,3,1,
+ 1,3,4,
+ 2,3,1,
+ 3,2,3,
+ 2,2,5,
+ 4,4,1,
+ 3,3,4,
+ 2,1,1,
+ 2,3,4,
+ 2,1,2,
+ 4,1,1,
+ 3,1,3,
+ 2,4,1,
+ 3,4,1,
+ 4,1,1,
+ 3,2,1,
+ 4,4,3,
+ 2,1,1,
+ 3,2,1,
+ 3,2,1),ncol=3,byrow=T)
> colnames(x)<-c("Chip A","Chip B","Chip C")
> 
> xtotab(x)
              1        2        3
Chip A 14.16667 24.66667 16.16667
Chip B 17.66667 18.16667 19.16667
Chip C 23.16667 12.16667 19.66667
> U(x)
           1         2          3
1 44.1666667 10.166667  0.6666667
2 10.1666667 37.666667  7.1666667
3  0.6666667  7.166667 47.1666667
> BlockAnalysis(x)
$Cri
         Location  Dispersion
Chip A  0.2981424 -2.06380040
Chip B  0.2236068  0.03762136
Chip C -0.5217492  2.02617904

$partition
           df            SS     pvalue
Location    2  4.111111e-01 0.81419486
Dispersion  2  8.366089e+00 0.01525200
Residual    0 -1.483258e-12         NA
Total       4  8.777200e+00 0.06691618

>