do.it<-function(n=20,p=5){

 # generate some fake data
 X=matrix(rnorm(n*p),n,p)
 b=sample(c(0.5,1,1.5,2,2.5,3),size=p,replace=TRUE)
 y=as.vector(X %*% b + rnorm(n))

 # take care of some data structure issues in R
 X=data.frame(X)
 dimnames(X)[[2]]<-paste('x',1:p,sep='')

 # fit a full model and a reduced model (__without last column__)
 obj =lm(as.formula(paste('y ~ ',paste('x',1:p,    sep='',collapse='+'))),data=X)
 obj0=lm(as.formula(paste('y ~ ',paste('x',1:(p-1),sep='',collapse='+'))),data=X)

 # look at the full model
 cat('**********full model**********\n\n')
 print(round(summary(obj)$coef,4))
 cat('\n')

 # look at the reduced model
 cat('**********reduced model**********\n\n')
 print(round(summary(obj0)$coef,4))
 cat('\n')

 # F-test (note p-q=1 here)
 numer=sum(obj0$resid^2)-sum(obj$resid^2)
 denom=sum(obj$resid^2)/(n-p-1)
 cat('**********F-test**********\n\n')
 cat('F-statistic = \t', round(numer/denom,4), '\n')

}

do.it()