Dec 11, 2014

## Inferring probabilities with a Beta prior, a third example of Bayesian calculations

In this post I will expand on a previous example of inferring probabilities from a data series. In particular, instead of considering a discrete set of candidate probabilities, I'll consider all (continuous) values between $$0$$ and $$1$$. This means our prior (and posterior) will now be a probability density function (pdf) instead of a probabilty mass function (pmf). More specifically, I'll use the Beta Distribution for this example.