In: Statistics and Probability
This is a question from Intro to Bayesian Statistics but I can't figure out what is expected here.
Derive the posterior distribution of obtaining heads in coin flips. The prior has p(θ = .25) = .25, p(θ = .50) = .50, and p(θ = .75) = .25. The data consist of a specific sequence of flips with 3 heads and 9 tails, so p(Data|θ) = θ^3 (1 − θ) ^9.