Abstract
Statistical hierarchical modelling is a powerful strategy to model complicated processes by a sequence of relatively simple models placed in a hierarchy. A hierarchical model includes the specification of the conditional probability density functions of response variables given candidate predictor variables, along with the specification of the probability density function of each single variable. We developed a statistical hierarchical model of the probability that a bacterial spore germinates, and used this model to predict the number of germinant spores as function of number of bacterial cells, nutrients concentration and amount of germination activation agents.