m = 0.5
n = 10
pr <- prior(m,n)
lk <- likelihood(N_samp,Y_samp)
po <- posterior(m,n,N_samp,Y_samp)
model_plot <- data.frame('Dist'=c(rep('Prior',nrow(pr)), 
rep('Likelihood',nrow(lk)), 
rep('Posterior',nrow(po))),
rbind(pr,lk,po))
with(model_plot, Dist <- factor(Dist, levels = c('Prior', 'Likelihood',
'Posterior'), ordered = TRUE))
mean_po <- mean_of_posterior(m,n,N_samp,Y_samp)
mode_po <- mode_of_posterior(m,n,N_samp,Y_samp)
sd_po <- sd_of_posterior(m,n,N_samp,Y_samp)</code>