Suppose that I have no knowledge of sampling methods and that I have some knowledge of probability theory (e.g. probability distribution and marginal distribution).
How would you explain the rejection sampling method in simple terms? Why do we need rejection sampling? What's its purpose (in particular, in the context of machine learning and Bayesian inference)?
There are other sampling methods. Why would one prefer rejection sampling (or not) over the other sampling methods?