Related Experiment Video
Updated: Apr 27, 2026

Holistic Facial Composite Creation and Subsequent Video Line-up Eyewitness Identification Paradigm
Published on: December 24, 2015
When 'neutral' evidence still has probative value (with implications from the Barry George Case)
Norman Fenton1, Daniel Berger1, David Lagnado2
1Queen Mary University of London, United Kingdom.
Abstract:
The likelihood ratio (LR) is a probabilistic method that has been championed as a 'simple rule' for evaluating the probative value of forensic evidence in court. Intuitively, if the LR is greater than one then the evidence supports the prosecution hypothesis; if the LR is less than one it supports the defence hypothesis, and if the LR is equal to one then the evidence favours neither (and so is considered 'neutral'-having no probative value). It can be shown by Bayes' theorem that this simple relationship only applies to pairs of hypotheses for which one is the negation of the other (i.e. to mutually exclusive and exhaustive hypotheses) and is not applicable otherwise. We show how easy it can be - even for evidence experts - to use pairs of hypotheses that they assume are mutually exclusive and exhaustive but are not, and hence to arrive at erroneous conclusions about the value of evidence using the LR. Furthermore, even when mutually exclusive and exhaustive hypotheses are used there are extreme restrictions as to what can be concluded about the probative value of evidence just from a LR. Most importantly, while the distinction between source-level hypotheses (such as defendant was/was not at the crime scene) and offence-level hypotheses (defendant is/is not guilty) is well known, it is not widely understood that a LR for evidence about the former generally has no bearing on the LR of the latter. We show for the first time (using Bayesian networks) the full impact of this problem, and conclude that it is only the LR of the offence level hypotheses that genuinely determines the probative value of the evidence. We investigate common scenarios in which evidence has a LR of one but still has significant probative value (i.e. is not neutral as is commonly assumed). As illustration we consider the ramifications of these points for the case of Barry George. The successful appeal against his conviction for the murder of Jill Dando was based primarily on the argument that the firearm discharge residue (FDR) evidence, assumed to support the prosecution hypothesis at the original trial, actually had a LR equal to one and hence was 'neutral'. However, our review of the appeal transcript shows numerous examples of the problems with the use of hypotheses identified above. We show that if one were to follow the arguments recorded in the Appeal judgement verbatim, then contrary to the Appeal conclusion, the probative value of the FDR evidence may not have been neutral as was concluded.
More Related Videos
09:09Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
Published on: September 27, 2024
06:42Continuous Theta Burst Stimulation of the Posterior Medial Frontal Cortex to Experimentally Reduce Ideological Threat Responses
Published on: September 28, 2018
Related Concept Videos
Statistical Significance
Decision Making: P-value Method
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim is also stated. These statements can act as null and alternative hypotheses: a null hypothesis would be a neutral statement while the alternative hypothesis can...
P-value
P-value stands for the probability value. P-value is the probability that, if the null hypothesis is true, the results from another randomly selected sample will be as extreme or more extreme as the results obtained from the given sample.
A large P-value calculated from the data indicates to not reject the null hypothesis. But a higher P-value does not mean that the null hypothesis is true. The smaller the P-value, the more...
Confirmation Biases
Null and Alternative Hypotheses
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
Significance Testing: Overview