y<-scan('A:/anova_anes.txt')
grp<-rep(c(1,2,3,4),c(5,7,9,8))
> grp
 [1] 1 1 1 1 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4

cbind(c(table(grp),length(grp)),
 round(c(mean(y[grp==1]),mean(y[grp==2]),mean(y[grp==3]),
    mean(y[grp==4]),mean(y)),2),
 round(c(var(y[grp==1]),var(y[grp==2]),var(y[grp==3]),
    var(y[grp==4]),var(y)),4) )
  [,1] [,2]   [,3]
1    5 4.64 1.2080
2    7 4.63 0.7390
3    9 3.53 0.2025
4    8 3.07 0.5479           #Table 3.3
    29 3.86 0.9924           


> fit<-lm(y~factor(grp))
> anova(fit)
Analysis of Variance Table

Response: y
            Df  Sum Sq Mean Sq F value   Pr(>F)   
factor(grp)  3 13.0670  4.3557  7.3969 0.001042   ## table 3.4
Residuals   25 14.7213  0.5889