Exercise

Exercise 7 - The Prior Distribution

Assume a Bayesian model sets the prior distribution for Florida's election night spread \(d\) to be normal with expected value \(\mu\) and standard deviation \(\tau\).

What are the interpretations of \(\mu\) and \(\tau\)?

Instructions

50 XP

Possible answers

\(\mu\) and \(\tau\) are arbitrary numbers that let us make probability statements about \(d\).

\(\mu\) and \(\tau\) summarize what we would predict for Florida before seeing any polls.

\(\mu\) and \(\tau\) summarize what we want to be true. We therefore set \(\mu\) at \(0.10\) and \(\tau\) at \(0.01\).

The choice of prior has no effect on the Bayesian analysis.