Methodologic procedure of beer competitions eliminating the problematic practices and based on the probabilistic approach

In beer competitions, there are some common problematic practices which ruin the final results, i.e. inappropriate distribution of samples into individual groups, inappropriate scoring of samples, comparison of results obtained from different sub-groups selecting better samples, inappropriate method of handling tied scores, and inappropriate numerical evaluation. To avoid these, the presented study aims to propose a methodologic procedure which eliminates these problematic practices and is based on the probabilistic approach. Further, it wishes to test and evaluate it by the Monte Carlo simulation. The procedure is based on a sensory evaluation of beer samples by assessors through ranking tests. Beer samples and assessors are randomly divided into groups in the lowest round of the competition. Data evaluation, which determines advancing samples or winners, is based on the application of the probability theory, namely the Bayesian theorem, so that the best-evaluated samples could be identified. This procedure achieves a higher probabilitiy of accurately recognised best-evaluated samples in comparison to the procedures involving the aforementioned problematic practices.