Visualizing Probabilistic Proof
Enrique Guerra-Pujol

TL;DR
This paper revisits the Blue Bus Problem, providing Bayesian solutions and visual representations to clarify probabilistic reasoning in legal contexts involving uncertain evidence.
Contribution
It introduces Bayesian methods and visual formats for analyzing the Blue Bus Problem, enhancing understanding of probabilistic proof in legal scenarios.
Findings
Bayesian solutions effectively model the Blue Bus Problem.
Visual representations improve comprehension of probabilistic reasoning.
The approach clarifies how evidence impacts probability assessments.
Abstract
The author revisits the Blue Bus Problem, a famous thought-experiment in law involving probabilistic proof, and presents simple Bayesian solutions to different versions of the blue bus hypothetical. In addition, the author expresses his solutions in standard and visual formats, i.e. in terms of probabilities and natural frequencies.
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Taxonomy
TopicsSemantic Web and Ontologies · Philosophy and History of Science · Probability and Statistical Research
