# A Bayesian network for modelling the Lady tasting tea experiment

## TL;DR

This paper introduces a Bayesian network to model a classic tea-tasting experiment, helping analyze how well someone can guess the preparation method of tea.

## Contribution

The novelty is a Bayesian Network model that calculates posterior probabilities of judgment outcomes based on the Lady's assumed ability levels.

## Key findings

- A Bayesian Network is proposed to model the Lady Tasting Tea experiment.
- The model calculates posterior probabilities based on three levels of the Lady's assumed ability.
- The BN provides a comprehensive inferential analysis of all possible data samples from the experiment.

## Abstract

A cup of tea can be made in one of the two ways: the milk or the tea infusion was first added to the cup. The Lady Tasting Tea experiment consists in mixing eight cups of tea, four in one way and four in the other, and presenting them to the Lady for judgment in a random order. This short article presents a Bayesian Network (BN) for modelling the Lady Tasting Tea experiment that provides a comprehensive perspective in inferential analysis of all the data samples possibly generated from the experiment. More specifically, with respect to a prior distribution of three possible levels (pure guessing, 75% sure, and 100% sure) of the Lady’s ability in correctly deciding how a served cup of tea has been made, the proposed BN model enables us to calculate the posterior probabilities of any judgment outcomes possibly made by the Lady.