model
{
    for (i in 1:n)
      {
         x[i]   ~  dnorm(mu,tau)     #  Likelihood function for each data point
       }
         mu     ~  dnorm(0,0.0001)   #  Prior for mu
         tau    <- 1/(sigma*sigma)   #  Prior for tau (as function of sigma)
         sigma  ~  dunif(0,20)       #  Prior for sigma
}