Judgements about probability shape our everyday lives, from deciding to bring an umbrella after reading the weather forecast, to weighing the risks of a medical treatment. In the courtroom, those judgements carry especially high stakes: misunderstanding the evidence can result in a false conviction or a false acquittal.

Courts routinely rely on legal decision-makers to interpret probabilistic evidence presented by forensic experts, yet this kind of reasoning can be challenging without statistical expertise. For example, while likelihood ratios are a common way of expressing the weight of forensic evidence, jurors often demonstrate poor comprehension of their meaning. Concerningly, sometimes jurors may even take a likelihood ratio to mean the opposite of what the expert intended. 

A further challenge relates to the accuracy and reliability of the forensic methods themselves. Experts are increasingly encouraged to report statistics about their accuracy, but there is limited research on how to communicate this information in a way non-experts can interpret. If statistics are not communicated clearly, judges, lawyers and jurors risk over- or undervaluing the evidence at hand. 

My PhD investigates when and why misunderstandings of statistics occur, and explores strategies to improve legal decision-makers' understanding of the statistics in forensic expert reports. 

More broadly, I am interested in applying cognitive theories to explore how people perceive and reason about numerical information. While I am currently focused on the legal and forensic context, the challenge of communicating probabilistic information is also highly relevant to areas such as medical decision-making, journalism and public education.