In this talk we will consider the classical Polya-Eggenberger-Friedman Urn Model and a generalization with infinitely many colors and we will show that in the balanced case the configuration of the urn after $n$ steps can be obtained by sampling an associated Markov chain at a random time which depends on $n$. We will show that most of the classical results can be derived easily using this...