model
{
	for(n in 1:20){
                      y[n] ~ dnorm(theta[n], tau.e)
		      theta[n] <- mu + a*Lect[n] + b*Test[n] + c*LT[n]
                      }
   mu~dnorm(0.0,1.0E-4)
   a~dnorm(0.0,1.0E-4)
   b~dnorm(0.0,1.0E-4)
   c~dnorm(0.0,1.0E-4)
   tau.e~dgamma(1.0E-3,1.0E-3); sigma.e <- 1.0/sqrt(tau.e)
}