9.10 Summary

• Built a simple Bayesian ormal regression model with quantitative response and predictor variables

• First example of a case where Markov Chain Monte Carlo simulation was really needed!

• Used simulated samples to summarize our posterior understanding of the relationship between response and predictor.

• Used simulated samples for posterior prediction.

9.10.1 You are not done yet!

• We have learned just enough to be dangerous!

• Review next chapter on evaluating the model before applying this new tool!