Elementary Statistics on Trial (the case of Lucia de Berk)

TL;DR

This paper critiques the use of a simple hypergeometric model in Lucia de Berk's case, highlighting how accounting for nurse variability significantly alters probability estimates and underscores the risks of oversimplified models.

Contribution

It demonstrates the impact of incorporating nurse-specific variability into statistical models used in legal cases, challenging previous simplified approaches.

Findings

Hypergeometric model underestimated incident probabilities.

Accounting for nurse variability increases probability estimates.

Simplistic models can lead to misleading legal conclusions.

Abstract

In the conviction of Lucia de Berk an important role was played by a simple hypergeometric model, used by the expert consulted by the court, which produced very small probabilities of occurrences of certain numbers of incidents. We want to draw attention to the fact that, if we take into account the variation among nurses in incidents they experience during their shifts, these probabilities can become considerably larger. This points to the danger of using an oversimplified discrete probability model in these circumstances.