> data=matrix(c(300,4,4,17,78,15,3,14,107,16,46,54,234,32,35,336),ncol=4,byrow=T)
> data
     [,1] [,2] [,3] [,4]
[1,]  300    4    4   17
[2,]   78   15    3   14
[3,]  107   16   46   54
[4,]  234   32   35  336
> chisq.test(data)

	Pearson's Chi-squared test

data:  data
X-squared = 407.8936, df = 9, p-value < 2.2e-16

> mu.x=rowSums(data)
> mu.x
[1] 325 110 223 637
> mu.y=colSums(data)
> mu.y
[1] 719  67  88 421
> n=sum(data)
> n
[1] 1295
> mu=matrix(nrow=4,ncol=4)
> for (i in 1:4) for (j in 1:4) mu[i,j]=mu.x[i]*mu.y[j]/n
> mu
          [,1]     [,2]      [,3]      [,4]
[1,] 180.44402 16.81467 22.084942 105.65637
[2,]  61.07336  5.69112  7.474903  35.76062
[3,] 123.81236 11.53745 15.153668  72.49653
[4,] 353.67027 32.95676 43.286486 207.08649
> g=matrix(nrow=4,ncol=4)
> for (i in 1:4) for (j in 1:4) g[i,j]=data[i,j]*log(data[i,j]/mu[i,j])
> g2=2*sum(g)
> g2
[1] 417.9889
> 1-pchisq(g2,9)
[1] 0
> q()
Save workspace image? [y/n/c]: n
