This technical note accompanies the case/class on "The Lady Tasting Tea" (LTT). It describes how a Bayesian would update his or her prior probability for the probability the LTT can correctly distinguish cups of tea based on whether the milk was added first or last. This long-form note describes both a discrete model (LTT has p of 0.5 or 0.8) and a more complicated continuous model (p is beta distributed). The abridged note (UVA-QA-0768) describes only the discrete model. The case/class itself provides a very useful analogy with which students can explore the elements of statistical inference.
