Statistical
Theatre: Misinterpretation of Quantitative Evidence in the Courtroom
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ABSTRACT:
The
increasing use of quantitative evidence in legal proceedings reflects a broader
shift towards data-informed forms of proof. Statistical analyses, probability
estimates, and forensic calculations are frequently presented as objective
indicators of truth; however, their evidential value depends not on the
mathematics itself, but on how the relationships they describe are interpreted.
This paper examines the misinterpretation of quantitative evidence in courtroom
settings, arguing that numerical outputs are often treated as conclusions
rather than as components of structured inference. Focusing on conditional
probability, the prosecutor’s fallacy, base rate neglect, witness testimony,
and DNA evidence, the paper demonstrates how common errors arise from a failure
to engage with the conditional and relational nature of probabilistic
reasoning. Consistent with earlier work highlighting the interpretive limits of
quantitative evidence, the analysis of key cases, including the Sally Clark
case and People v Collins, together with contemporary examples drawn from
forensic science and algorithmic decision-making, demonstrates how numerical
evidence can assume persuasive authority that exceeds its probative value when
underlying assumptions are not made explicit.Building on established scholarship concerning the persuasive
authority of numerical evidence, expert testimony, and probabilistic reasoning
in legal decision-making, this paper proposes the Statistical Theatre Model to
describe situations in which quantitative evidence acquires persuasive force
independent of its inferential value.The paper further considers cognitive and
institutional factors that contribute to these errors and argues that
improvement lies not in increased mathematical complexity, but in greater
conceptual clarity. In addition to identifying common interpretive failures,
the paper proposes practical reforms to improve the communication and
evaluation of quantitative evidence by experts, lawyers, judges, and jurors. In
doing so, it highlights the importance of aligning the presentation of
quantitative evidence with the interpretive demands of legal decision-making.
Statistical evidence must remain a tool of inference rather than an unwarranted
source of certainty.
Keywords:
Statistical
evidence; Conditional
probability; Prosecutor’s
fallacy; Base
rate neglect;
DNA evidence; Witness
testimony;
Bayesian reasoning; Legal
decision-making; Statistical
independence; Likelihood
ratios